CartPole_FCSNN.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Singular-Brain/DeepBioLCNet/blob/main/CartPole_FCSNN.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7fTSvrK3T_GA"
      },
      "source": [
        "#Notebook setups"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "lXtgP_iEPE0G",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b2f7e1cf-7ffd-4031-c746-d602c68ed0ce"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[K     |████████████████████████████████| 831.4 MB 2.7 kB/s \n",
            "\u001b[K     |████████████████████████████████| 22.1 MB 1.2 MB/s \n",
            "\u001b[K     |████████████████████████████████| 120 kB 85.6 MB/s \n",
            "\u001b[K     |████████████████████████████████| 74 kB 4.0 MB/s \n",
            "\u001b[K     |████████████████████████████████| 296 kB 88.6 MB/s \n",
            "\u001b[K     |████████████████████████████████| 38.1 MB 1.3 MB/s \n",
            "\u001b[?25h  Building wheel for BindsNET (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "torchtext 0.11.0 requires torch==1.10.0, but you have torch 1.9.0 which is incompatible.\n",
            "torchaudio 0.10.0+cu111 requires torch==1.10.0, but you have torch 1.9.0 which is incompatible.\n",
            "datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.\n",
            "albumentations 0.1.12 requires imgaug<0.2.7,>=0.2.5, but you have imgaug 0.2.9 which is incompatible.\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "!pip install -q git+https://github.com/Singular-Brain/DeepBioLCNet"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "KXcXvvsXcOlv"
      },
      "outputs": [],
      "source": [
        "# !git clone https://github.com/Singular-Brain/DeepBioLCNet\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "### gym and colab compatibility\n",
        "\n",
        "# !apt-get install -y xvfb python-opengl > /dev/null 2>&1\n",
        "# !pip install gym pyvirtualdisplay > /dev/null 2>&1\n",
        "\n",
        "import gym\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "# from IPython import display as ipythondisplay\n",
        "\n",
        "# from pyvirtualdisplay import Display\n",
        "# display = Display(visible=0, size=(400, 300))\n",
        "# display.start()"
      ],
      "metadata": {
        "id": "0QFC6xL2uAaF"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "K4l3AVRbGS4Q"
      },
      "outputs": [],
      "source": [
        "import torch\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from itertools import count\n",
        "from matplotlib.axes import Axes\n",
        "from matplotlib.image import AxesImage\n",
        "from torch.nn.modules.utils import _pair\n",
        "from matplotlib.collections import PathCollection\n",
        "from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
        "from typing import Tuple, List, Optional, Sized, Dict, Union\n",
        "import math\n",
        "import random\n",
        "from torchvision.transforms.functional import crop\n",
        "# from ..utils import reshape_locally_connected_weights, reshape_locally_connected_weights_meh, reshape_conv2d_weights\n",
        "\n",
        "import gym\n",
        "import tkinter\n",
        "\n",
        "from PIL import Image\n",
        "from collections import namedtuple"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "BFGNAecpT-Lj"
      },
      "outputs": [],
      "source": [
        "from bindsnet.network.nodes import Nodes\n",
        "import os\n",
        "### import torch\n",
        "import numpy as np\n",
        "import copy\n",
        "import math\n",
        "import matplotlib.pyplot as plt\n",
        "import collections\n",
        "from torchvision import transforms\n",
        "from tqdm.notebook import tqdm\n",
        "\n",
        "from sklearn.metrics import confusion_matrix\n",
        "import seaborn as sn\n",
        "import torch.nn.functional as fn\n",
        "\n",
        "from abc import ABC, abstractmethod\n",
        "from typing import Union, Tuple, Optional, Sequence\n",
        "from torch.nn.modules.utils import _pair\n",
        "\n",
        "from bindsnet.datasets import MNIST\n",
        "from bindsnet.encoding import PoissonEncoder\n",
        "from bindsnet.network import Network\n",
        "from bindsnet.network.nodes import Input, LIFNodes, AdaptiveLIFNodes, IFNodes\n",
        "from bindsnet.network.topology import Connection, MaxPool2dLocalConnection\n",
        "from bindsnet.network.topology import LocalConnection, LocalConnectionOrig\n",
        "from bindsnet.network.monitors import Monitor, AbstractMonitor, TensorBoardMonitor\n",
        "from bindsnet.learning import PostPre, MSTDP, MSTDPET, WeightDependentPostPre, Hebbian\n",
        "from bindsnet.learning.reward import DynamicDopamineInjection, DopaminergicRPE, AbstractReward\n",
        "from bindsnet.analysis.plotting import plot_locally_connected_weights,plot_locally_connected_weights_meh,plot_spikes,\\\n",
        "plot_LC_timepoint_spikes,plot_locally_connected_weights_meh2,plot_convergence_and_histogram,plot_locally_connected_weights_meh3\n",
        "from bindsnet.analysis.visualization import plot_weights_movie, plot_spike_trains_for_example,summary, plot_voltage\n",
        "from bindsnet.utils import reshape_locally_connected_weights, reshape_locally_connected_weights_meh, reshape_conv2d_weights"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "class RLTasks(AbstractReward):\n",
        "    # language=rst\n",
        "    \"\"\"\n",
        "    Computes the reward for a given RL task in the current state\n",
        "    \"\"\"\n",
        "    def __init__(\n",
        "        self,\n",
        "        env_id,\n",
        "        **kwargs,\n",
        "    ) -> None:\n",
        "\n",
        "        super().__init__()\n",
        "\n",
        "        if env_id == \"CartPole-v0\":\n",
        "            self.compute = self._cartPole_compute\n",
        "        elif env_id == \"MountainCar-v0-v0\":\n",
        "            self.compute = self._mountainCar_compute\n",
        "        elif env_id == \"BreakoutDeterministic-v4\":\n",
        "            self.compute = self._breakout_compute\n",
        "        else:\n",
        "            raise NotImplementedError(\n",
        "                \"This rl environment is not currently supported.\"\n",
        "            )\n",
        "    \n",
        "    def _cartPole_compute(self, **kwargs):\n",
        "        success = kwargs['success']\n",
        "        failure = kwargs['failure']\n",
        "        if kwargs['classic_reward']:\n",
        "            if failure:\n",
        "                return torch.tensor([0.])\n",
        "            else:\n",
        "                return torch.tensor([1.])\n",
        "\n",
        "        env = kwargs['env']\n",
        "        state = env.state\n",
        "        success = kwargs['success']\n",
        "        failure = kwargs['failure']\n",
        "        x, x_dot, theta, theta_dot = state\n",
        "        # r1 = (env.x_threshold - abs(x)) / env.x_threshold - 0.8\n",
        "        # r2 = ((env.theta_threshold_radians - abs(theta)) / env.theta_threshold_radians - 0.5)#*2\n",
        "        #reward = r1 + r2\n",
        "        reward = ((env.theta_threshold_radians - abs(theta)) / env.theta_threshold_radians) #- 0.5*abs(theta_dot)\n",
        "        if success:\n",
        "            reward += 5\n",
        "        elif failure:\n",
        "            reward -= 5\n",
        "        reward = torch.tensor([reward])\n",
        "        return reward\n",
        "\n",
        "    def _mountainCar_compute(self):\n",
        "        pass\n",
        "\n",
        "    def _breakout_compute(self):\n",
        "        pass\n",
        "        \n",
        "    def update(self):\n",
        "        pass\n",
        "\n",
        "    def online_compute(self,):\n",
        "        pass"
      ],
      "metadata": {
        "id": "WqFD8yro6WCb"
      },
      "execution_count": 71,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ULGGHW43UksI"
      },
      "source": [
        "## Sets up Gpu use and manual seed\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 72,
      "metadata": {
        "id": "LiUmFrpcUfmR",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ace1fc67-264b-4310-95ea-f3b4d266c0f2"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Running on Device =  cuda\n"
          ]
        }
      ],
      "source": [
        "if torch.cuda.is_available():\n",
        "    device =  torch.device(\"cuda\")\n",
        "    gpu = True\n",
        "else:\n",
        "    device =  torch.device(\"cpu\")\n",
        "    gpu = False\n",
        "\n",
        "def manual_seed(seed):\n",
        "    random.seed(seed)\n",
        "    torch.manual_seed(seed)\n",
        "    np.random.seed(seed)\n",
        "    if torch.cuda.is_available():\n",
        "        torch.cuda.manual_seed_all(seed)\n",
        "\n",
        "\n",
        "SEED = 2045 # The Singularity is Near!\n",
        "manual_seed(SEED)\n",
        "WANDB = False\n",
        "\n",
        "torch.set_num_threads(os.cpu_count() - 1)\n",
        "print(\"Running on Device = \", device)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MBKedMpIleMr"
      },
      "source": [
        "# Custom Monitors"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6tfqpsr2a1WV"
      },
      "source": [
        "## Reward Monitor"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 73,
      "metadata": {
        "id": "M44GJ65GleMs"
      },
      "outputs": [],
      "source": [
        "class RewardMonitor(AbstractMonitor):\n",
        "    # language=rst\n",
        "    \"\"\"\n",
        "    Records state variables of interest.\n",
        "    \"\"\"\n",
        "\n",
        "    def __init__(\n",
        "        self,\n",
        "        time: None,\n",
        "        batch_size: int = 1,\n",
        "        device: str = \"cpu\",\n",
        "    ):\n",
        "        # language=rst\n",
        "        \"\"\"\n",
        "        Constructs a ``Monitor`` object.\n",
        "\n",
        "        :param obj: An object to record state variables from during network simulation.\n",
        "        :param state_vars: Iterable of strings indicating names of state variables to record.\n",
        "        :param time: If not ``None``, pre-allocate memory for state variable recording.\n",
        "        :param device: Allow the monitor to be on different device separate from Network device\n",
        "        \"\"\"\n",
        "        super().__init__()\n",
        "\n",
        "        self.time = time\n",
        "        self.batch_size = batch_size\n",
        "        self.device = device\n",
        "\n",
        "        # if time is not specified the monitor variable accumulate the logs\n",
        "        if self.time is None:\n",
        "            self.device = \"cpu\"\n",
        "\n",
        "        self.recording = []\n",
        "        self.reset_state_variables()\n",
        "\n",
        "    def get(self,) -> torch.Tensor:\n",
        "        # language=rst\n",
        "        \"\"\"\n",
        "        Return recording to user.\n",
        "\n",
        "        :return: Tensor of shape ``[time, n_1, ..., n_k]``, where ``[n_1, ..., n_k]`` is the shape of the recorded state\n",
        "        variable.\n",
        "        Note, if time == `None`, get return the logs and empty the monitor variable\n",
        "\n",
        "        \"\"\"\n",
        "        # return_logs = torch.as_tensor(self.recording)\n",
        "        # if self.time is None:\n",
        "        #     self.recording = []\n",
        "        return self.recording\n",
        "\n",
        "    def record(self, **kwargs) -> None:\n",
        "        # language=rst\n",
        "        \"\"\"\n",
        "        Appends the current value of the recorded state variables to the recording.\n",
        "        \"\"\"\n",
        "        if \"reward\" in kwargs:\n",
        "            self.recording.append(kwargs[\"reward\"])\n",
        "        # remove the oldest element (first in the list)\n",
        "        # if self.time is not None:\n",
        "        #     self.recording.pop(0)\n",
        "\n",
        "    def reset_state_variables(self) -> None:\n",
        "        # language=rst\n",
        "        \"\"\"\n",
        "        Resets recordings to empty ``List``s.\n",
        "        \"\"\"\n",
        "        self.recording = []\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8clxN_npa1WY"
      },
      "source": [
        "## Plot Eligibility trace"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 74,
      "metadata": {
        "id": "SshGlRwpa1WZ"
      },
      "outputs": [],
      "source": [
        "class PlotET(AbstractMonitor):\n",
        "    # language=rst\n",
        "    \"\"\"\n",
        "    Records state variables of interest.\n",
        "    \"\"\"\n",
        "\n",
        "    def __init__(\n",
        "        self,\n",
        "        i,\n",
        "        j,\n",
        "        source,\n",
        "        target,\n",
        "        connection,\n",
        "    ):\n",
        "        # language=rst\n",
        "        \"\"\"\n",
        "        Constructs a ``Monitor`` object.\n",
        "\n",
        "        :param obj: An object to record state variables from during network simulation.\n",
        "        :param state_vars: Iterable of strings indicating names of state variables to record.\n",
        "        :param time: If not ``None``, pre-allocate memory for state variable recording.\n",
        "        :param device: Allow the monitor to be on different device separate from Network device\n",
        "        \"\"\"\n",
        "        super().__init__()\n",
        "        self.i = i\n",
        "        self.j = j\n",
        "        self.source = source\n",
        "        self.target = target\n",
        "        self.connection = connection\n",
        "\n",
        "        self.reset_state_variables()\n",
        "\n",
        "    def get(self,) -> torch.Tensor:\n",
        "        # language=rst\n",
        "        \"\"\"\n",
        "        Return recording to user.\n",
        "\n",
        "        :return: Tensor of shape ``[time, n_1, ..., n_k]``, where ``[n_1, ..., n_k]`` is the shape of the recorded state\n",
        "        variable.\n",
        "        Note, if time == `None`, get return the logs and empty the monitor variable\n",
        "\n",
        "        \"\"\"\n",
        "        # return_logs = torch.as_tensor(self.recording)\n",
        "        # if self.time is None:\n",
        "        #     self.recording = []\n",
        "        return self.recording\n",
        "\n",
        "    def record(self, **kwargs) -> None:\n",
        "        # language=rst\n",
        "        \"\"\"\n",
        "        Appends the current value of the recorded state variables to the recording.\n",
        "        \"\"\"\n",
        "        if hasattr(self.connection.update_rule, 'p_plus'):\n",
        "            self.recording['spikes_i'].append(self.source.s.ravel()[self.i].item())\n",
        "            self.recording['spikes_j'].append(self.target.s.ravel()[self.j].item())\n",
        "            self.recording['p_plus'].append(self.connection.update_rule.p_plus[self.i].item())\n",
        "            self.recording['p_minus'].append(self.connection.update_rule.p_minus[self.j].item())\n",
        "            self.recording['eligibility'].append(self.connection.update_rule.eligibility[self.i,self.j].item())\n",
        "            self.recording['eligibility_trace'].append(self.connection.update_rule.eligibility_trace[self.i,self.j].item())\n",
        "            self.recording['w'].append(self.connection.w[self.i,self.j].item())\n",
        "\n",
        "    def plot(self):\n",
        "\n",
        "        fig, axs  = plt.subplots(7)\n",
        "        fig.set_size_inches(10, 20)\n",
        "        for i, (name, p) in enumerate(self.recording.items()):\n",
        "            axs[i].plot(p[-250:])\n",
        "            axs[i].set_title(name)\n",
        "    \n",
        "        fig.show()\n",
        "\n",
        "    def reset_state_variables(self) -> None:\n",
        "        # language=rst\n",
        "        \"\"\"\n",
        "        Resets recordings to empty ``List``s.\n",
        "        \"\"\"\n",
        "        self.recording = {\n",
        "        'spikes_i': [],\n",
        "        'spikes_j': [],\n",
        "        'p_plus':[],\n",
        "        'p_minus':[],\n",
        "        'eligibility':[],\n",
        "        'eligibility_trace':[],\n",
        "        'w': [],\n",
        "        }\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "R_YGE1XjvIkZ"
      },
      "source": [
        "## Kernel "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 75,
      "metadata": {
        "id": "-4hp2V46vOUv"
      },
      "outputs": [],
      "source": [
        "class AbstractKernel(ABC):\n",
        "    def __init__(self, kernel_size):\n",
        "        \"\"\"\n",
        "        Base class for generating image filter kernels such as Gabor, DoG, etc. Each subclass should override :attr:`__call__` function.\n",
        "        Instantiates a ``Filter Kernel`` object.\n",
        "        :param window_size : The size of the kernel (int)\n",
        "        \"\"\"\n",
        "        self.window_size = kernel_size\n",
        "\n",
        "    def __call__(self):\n",
        "        pass\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 76,
      "metadata": {
        "id": "PL2L6_ABwBH4"
      },
      "outputs": [],
      "source": [
        "class DoGKernel(AbstractKernel):\n",
        "    def __init__(self, kernel_size: Union[int, Tuple[int, int]], sigma1 : float, sigma2 : float):\n",
        "        \"\"\"\n",
        "        Generates DoG filter kernels.\n",
        "        :param kernel_size: Horizontal and vertical size of DOG kernels.(If pass int, we consider it as a square filter) \n",
        "        :param sigma1 : The sigma parameter for the first Gaussian function.\n",
        "        :param sigma2 : The sigma parameter for the second Gaussian function.\n",
        "        \"\"\"\n",
        "        super(DoGKernel, self).__init__(kernel_size)\n",
        "        self.sigma1 = sigma1\n",
        "        self.sigma2 = sigma2\n",
        "        \n",
        "    def __call__(self):\n",
        "        k = self.window_size//2\n",
        "        x, y = np.mgrid[-k:k+1:1, -k:k+1:1]\n",
        "        a = 1.0 / (2 * math.pi)\n",
        "        prod = x*x + y*y\n",
        "        f1 = (1/(self.sigma1*self.sigma1)) * np.exp(-0.5 * (1/(self.sigma1*self.sigma1)) * (prod))\n",
        "        f2 = (1/(self.sigma2*self.sigma2)) * np.exp(-0.5 * (1/(self.sigma2*self.sigma2)) * (prod))\n",
        "        dog = a * (f1-f2)\n",
        "        dog_mean = np.mean(dog)\n",
        "        dog = dog - dog_mean\n",
        "        dog_max = np.max(dog)\n",
        "        dog = dog / dog_max\n",
        "        dog_tensor = torch.from_numpy(dog)\n",
        "        # returns a 2d tensor corresponding to the requested DoG filter\n",
        "        return dog_tensor.float()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 77,
      "metadata": {
        "id": "zBUT0IUZDXxW"
      },
      "outputs": [],
      "source": [
        "class Filter():\n",
        "    \"\"\"\n",
        "    Applies a filter transform. Each filter contains a sequence of :attr:`FilterKernel` objects.\n",
        "    The result of each filter kernel will be passed through a given threshold (if not :attr:`None`).\n",
        "    Args:\n",
        "        filter_kernels (sequence of FilterKernels): The sequence of filter kernels.\n",
        "        padding (int, optional): The size of the padding for the convolution of filter kernels. Default: 0\n",
        "        thresholds (sequence of floats, optional): The threshold for each filter kernel. Default: None\n",
        "        use_abs (boolean, optional): To compute the absolute value of the outputs or not. Default: False\n",
        "    .. note::\n",
        "        The size of the compund filter kernel tensor (stack of individual filter kernels) will be equal to the \n",
        "        greatest window size among kernels. All other smaller kernels will be zero-padded with an appropriate \n",
        "        amount.\n",
        "    \"\"\"\n",
        "    # filter_kernels must be a list of filter kernels\n",
        "    # thresholds must be a list of thresholds for each kernel\n",
        "    def __init__(self, filter_kernels, padding=0, thresholds=None, use_abs=False):\n",
        "        tensor_list = []\n",
        "        self.max_window_size = 0\n",
        "        for kernel in filter_kernels:\n",
        "            if isinstance(kernel, torch.Tensor):\n",
        "                tensor_list.append(kernel)\n",
        "                self.max_window_size = max(self.max_window_size, kernel.size(-1))\n",
        "            else:\n",
        "                tensor_list.append(kernel().unsqueeze(0))\n",
        "                self.max_window_size = max(self.max_window_size, kernel.window_size)\n",
        "        for i in range(len(tensor_list)):\n",
        "            p = (self.max_window_size - filter_kernels[i].window_size)//2\n",
        "            tensor_list[i] = fn.pad(tensor_list[i], (p,p,p,p))\n",
        "\n",
        "        self.kernels = torch.stack(tensor_list)\n",
        "        self.number_of_kernels = len(filter_kernels)\n",
        "        self.padding = padding\n",
        "        if isinstance(thresholds, list):\n",
        "            self.thresholds = thresholds.clone().detach()\n",
        "            self.thresholds.unsqueeze_(0).unsqueeze_(2).unsqueeze_(3)\n",
        "        else:\n",
        "            self.thresholds = thresholds\n",
        "        self.use_abs = use_abs\n",
        "\n",
        "    # returns a 4d tensor containing the flitered versions of the input image\n",
        "    # input is a 4d tensor. dim: (minibatch=1, filter_kernels, height, width)\n",
        "    def __call__(self, input):\n",
        "\n",
        "        # if input.dim() == 3:\n",
        "        #     input2 = torch.unsqueeze(input, 0)\n",
        "        input.unsqueeze_(0)\n",
        "        output = fn.conv2d(input, self.kernels, padding = self.padding).float()\n",
        "        if not(self.thresholds is None):\n",
        "            output = torch.where(output < self.thresholds, torch.tensor(0.0, device=output.device), output)\n",
        "        if self.use_abs:\n",
        "            torch.abs_(output)\n",
        "        return output.squeeze(0)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sCXSLZZoGS4z"
      },
      "source": [
        "# Viz"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 78,
      "metadata": {
        "id": "3DIAdG1mGS4z"
      },
      "outputs": [],
      "source": [
        "def plot_LC_timepoint_spikes(spikes: torch.Tensor,\n",
        "    timepoint: int,\n",
        "    n_filters: int,\n",
        "    in_chans: int,\n",
        "    slice_to_plot: int,\n",
        "    conv_size: Union[int, Tuple[int, int]],\n",
        "    im: Optional[AxesImage] = None,\n",
        "    lines: bool = True,\n",
        "    figsize: Tuple[int, int] = (10, 10),\n",
        "    cmap: str = \"hot_r\",\n",
        "    color: str='r'\n",
        "    ):\n",
        "    # language=rst\n",
        "    \"\"\"\n",
        "    \"\"\"\n",
        "\n",
        "    n_sqrt = int(np.ceil(np.sqrt(n_filters)))\n",
        "    sel_slice = spikes[timepoint].view(in_chans, n_filters, conv_size, conv_size).cpu()\n",
        "    sel_slice = sel_slice[slice_to_plot, ...].view(n_filters, conv_size, conv_size)\n",
        "    spikes_ = np.zeros((n_sqrt*conv_size, n_sqrt*conv_size))\n",
        "    filt_counter = 0\n",
        "\n",
        "    fig, ax = plt.subplots(figsize=figsize)\n",
        "\n",
        "    for n1 in range(n_sqrt):\n",
        "        for n2 in range(n_sqrt):\n",
        "            filter_ = sel_slice[filt_counter, :, :].view(conv_size, conv_size)\n",
        "            spikes_[n1 * conv_size : (n1 + 1) * conv_size, n2 * conv_size : (n2 + 1) * conv_size] = filter_\n",
        "            filt_counter += 1\n",
        "            ax.axhline((n1 + 1) * conv_size, color=\"g\", linestyle=\"-\")\n",
        "            ax.axvline((n2 + 1) * conv_size, color=\"g\", linestyle=\"--\")\n",
        "    ax.imshow(spikes_, cmap='Greys')\n",
        "    return spikes_\n",
        "    \n",
        "def plot_FC_response_map(lc: object,\n",
        "    fc: object,\n",
        "    ind_neuron_in_group: int,\n",
        "    label: int,\n",
        "    n_per_action: int,\n",
        "    input_channel: int = 0,\n",
        "    scale_factor: float = 1.0,\n",
        "    lines: bool = True,\n",
        "    figsize: Tuple[int, int] = (5, 5),\n",
        "    cmap: str = \"hot_r\",\n",
        "    color: str='r'\n",
        "    ) -> AxesImage:\n",
        "    # language=rst\n",
        "    \"\"\"\n",
        "    Plot a connection weight matrix of a :code:`Connection` with `locally connected\n",
        "    structure <http://yann.lecun.com/exdb/publis/pdf/gregor-nips-11.pdf>_.\n",
        "    :param lc: LC connection object of LCNet\n",
        "    :param fc: FC connection object of LCNet\n",
        "    :param input_channel: indicates weights which connected to this channel of input\n",
        "    :param scale_factor: determines intensity of activation map  \n",
        "    :param lines: Whether or not to draw horizontal and vertical lines separating input regions.\n",
        "    :param figsize: Horizontal, vertical figure size in inches.\n",
        "    :param cmap: Matplotlib colormap.\n",
        "    :return: Used for re-drawing the weights plot.\n",
        "    \"\"\"\n",
        "\n",
        "    n_sqrt = int(np.ceil(np.sqrt(lc.out_channels)))\n",
        "\n",
        "    sel_slice = lc.w.view(lc.in_channels, lc.out_channels, lc.conv_size[0], lc.conv_size[1], lc.kernel_size[0], lc.kernel_size[1]).cpu()\n",
        "    sel_slice = sel_slice[input_channel, ...]\n",
        "    input_size = _pair(int(np.sqrt(lc.source.n)))\n",
        "    reshaped = reshape_LC_weights(sel_slice, lc.out_channels, lc.kernel_size, lc.conv_size, input_size)\n",
        "\t\n",
        "    ind_neuron = label * n_per_action + ind_neuron_in_group\n",
        "    w = fc.w[:,ind_neuron].view(reshaped.shape[0]//lc.kernel_size[0],reshaped.shape[1]//lc.kernel_size[1])\n",
        "    w = w.clip(lc.wmin,lc.wmax).repeat_interleave(lc.kernel_size[0], dim=0).repeat_interleave(lc.kernel_size[1], dim=1).cpu()\n",
        "\n",
        "    fig, ax = plt.subplots(figsize=figsize)\n",
        "\n",
        "    im = ax.imshow(reshaped.cpu()*w, cmap=cmap, vmin=lc.wmin, vmax=lc.wmax)\n",
        "    div = make_axes_locatable(ax)\n",
        "    cax = div.append_axes(\"right\", size=\"5%\", pad=0.05)\n",
        "\n",
        "    if lines:\n",
        "        for i in range(\n",
        "            n_sqrt * lc.kernel_size[0],\n",
        "            n_sqrt * lc.conv_size[0] * lc.kernel_size[0],\n",
        "            n_sqrt * lc.kernel_size[0],\n",
        "        ):\n",
        "            ax.axhline(i - 0.5, color=color, linestyle=\"--\")\n",
        "\n",
        "        for i in range(\n",
        "            n_sqrt * lc.kernel_size[1],\n",
        "            n_sqrt * lc.conv_size[1] * lc.kernel_size[1],\n",
        "            n_sqrt * lc.kernel_size[1],\n",
        "        ):\n",
        "            ax.axvline(i - 0.5, color=color, linestyle=\"--\")\n",
        "\n",
        "    ax.set_xticks(())\n",
        "    ax.set_yticks(())\n",
        "    ax.set_aspect(\"auto\")\n",
        "\n",
        "    plt.colorbar(im, cax=cax)\n",
        "    fig.tight_layout()\n",
        "\n",
        "    return im\n",
        "\n",
        "def plot_LC_activation_map(lc : object,\n",
        "    spikes: torch.tensor,\n",
        "    input_channel: int = 0,\n",
        "    scale_factor: float = 1.0,\n",
        "    lines: bool = True,\n",
        "    figsize: Tuple[int, int] = (5, 5),\n",
        "    cmap: str = \"hot_r\",\n",
        "    color: str='r'\n",
        "    ) -> AxesImage:\n",
        "    # language=rst\n",
        "    \"\"\"\n",
        "    Plot an activation map of a :code:`Connection` with `locally connected\n",
        "    structure <http://yann.lecun.com/exdb/publis/pdf/gregor-nips-11.pdf>_.\n",
        "    :param lc: LC connection object of LCNet\n",
        "    :param input_channel: indicates weights which connected to this channel of input \n",
        "    :param scale_factor: determines intensity of activation map \n",
        "    :param lines: Whether or not to draw horizontal and vertical lines separating input regions.\n",
        "    :param figsize: Horizontal, vertical figure size in inches.\n",
        "    :param cmap: Matplotlib colormap.\n",
        "    :return: Used for re-drawing the weights plot.\n",
        "    \"\"\"\n",
        "    spikes = spikes.sum(0).squeeze().view(lc.conv_size[0]*int(np.sqrt(lc.out_channels)),lc.conv_size[1]*int(np.sqrt(lc.out_channels)))\n",
        "    x = scale_factor * spikes / torch.max(spikes)\n",
        "    x = x.clip(lc.wmin,lc.wmax).repeat_interleave(lc.kernel_size[0], dim=0).repeat_interleave(lc.kernel_size[1], dim=1).cpu()\n",
        "    n_sqrt = int(np.ceil(np.sqrt(lc.out_channels)))\n",
        "\n",
        "    sel_slice = lc.w.view(lc.in_channels, lc.out_channels, lc.conv_size[0], lc.conv_size[1], lc.kernel_size[0], lc.kernel_size[1]).cpu()\n",
        "    sel_slice = sel_slice[input_channel, ...]\n",
        "    input_size = _pair(int(np.sqrt(lc.source.n)))\n",
        "    reshaped = reshape_LC_weights(sel_slice, lc.out_channels, lc.kernel_size, lc.conv_size, input_size)\n",
        "\n",
        "    fig, ax = plt.subplots(figsize=figsize)\n",
        "\n",
        "    im = ax.imshow(reshaped.cpu()*x, cmap=cmap, vmin=lc.wmin, vmax=lc.wmax)\n",
        "    div = make_axes_locatable(ax)\n",
        "    cax = div.append_axes(\"right\", size=\"5%\", pad=0.05)\n",
        "\n",
        "    if lines:\n",
        "        for i in range(\n",
        "            n_sqrt * lc.kernel_size[0],\n",
        "            n_sqrt * lc.conv_size[0] * lc.kernel_size[0],\n",
        "            n_sqrt * lc.kernel_size[0],\n",
        "        ):\n",
        "            ax.axhline(i - 0.5, color=color, linestyle=\"--\")\n",
        "\n",
        "        for i in range(\n",
        "            n_sqrt * lc.kernel_size[1],\n",
        "            n_sqrt * lc.conv_size[1] * lc.kernel_size[1],\n",
        "            n_sqrt * lc.kernel_size[1],\n",
        "        ):\n",
        "            ax.axvline(i - 0.5, color=color, linestyle=\"--\")\n",
        "\n",
        "    ax.set_xticks(())\n",
        "    ax.set_yticks(())\n",
        "    ax.set_aspect(\"auto\")\n",
        "\n",
        "    plt.colorbar(im, cax=cax)\n",
        "    fig.tight_layout()\n",
        "\n",
        "    return im\n",
        "\n",
        "\n",
        "def reshape_LC_weights(\n",
        "    w: torch.Tensor,\n",
        "    n_filters: int,\n",
        "    kernel_size: Union[int, Tuple[int, int]],\n",
        "    conv_size: Union[int, Tuple[int, int]],\n",
        "    input_sqrt: Union[int, Tuple[int, int]],\n",
        ") -> torch.Tensor:\n",
        "    # language=rst\n",
        "    \"\"\"\n",
        "    Get the weights from a locally connected layer and reshape them to be two-dimensional and square.\n",
        "    :param w: Weights from a locally connected layer.\n",
        "    :param n_filters: No. of neuron filters.\n",
        "    :param kernel_size: Side length(s) of convolutional kernel.\n",
        "    :param conv_size: Side length(s) of convolution population.\n",
        "    :param input_sqrt: Sides length(s) of input neurons.\n",
        "    :return: Locally connected weights reshaped as a collection of spatially ordered square grids.\n",
        "    \"\"\"\n",
        "    k1, k2 = kernel_size\n",
        "    c1, c2 = conv_size\n",
        "    i1, i2 = input_sqrt\n",
        "    c1sqrt, c2sqrt = int(math.ceil(math.sqrt(c1))), int(math.ceil(math.sqrt(c2)))\n",
        "    fs = int(math.ceil(math.sqrt(n_filters)))\n",
        "\n",
        "    w_ = torch.zeros((n_filters * k1, k2 * c1 * c2))\n",
        "\n",
        "    for n1 in range(c1):\n",
        "        for n2 in range(c2):\n",
        "            for feature in range(n_filters):\n",
        "                n = n1 * c2 + n2\n",
        "                filter_ = w[feature, n1, n2, :, :\n",
        "                ].view(k1, k2)\n",
        "                w_[feature * k1 : (feature + 1) * k1, n * k2 : (n + 1) * k2] = filter_\n",
        "\n",
        "    if c1 == 1 and c2 == 1:\n",
        "        square = torch.zeros((i1 * fs, i2 * fs))\n",
        "\n",
        "        for n in range(n_filters):\n",
        "            square[\n",
        "                (n // fs) * i1 : ((n // fs) + 1) * i2,\n",
        "                (n % fs) * i2 : ((n % fs) + 1) * i2,\n",
        "            ] = w_[n * i1 : (n + 1) * i2]\n",
        "\n",
        "        return square\n",
        "    else:\n",
        "        square = torch.zeros((k1 * fs * c1, k2 * fs * c2))\n",
        "\n",
        "        for n1 in range(c1):\n",
        "            for n2 in range(c2):\n",
        "                for f1 in range(fs):\n",
        "                    for f2 in range(fs):\n",
        "                        if f1 * fs + f2 < n_filters:\n",
        "                            square[\n",
        "                                k1 * (n1 * fs + f1) : k1 * (n1 * fs + f1 + 1),\n",
        "                                k2 * (n2 * fs + f2) : k2 * (n2 * fs + f2 + 1),\n",
        "                            ] = w_[\n",
        "                                (f1 * fs + f2) * k1 : (f1 * fs + f2 + 1) * k1,\n",
        "                                (n1 * c2 + n2) * k2 : (n1 * c2 + n2 + 1) * k2,\n",
        "                            ]\n",
        "\n",
        "        return square\n",
        "\n",
        "def plot_semantic_pooling(lc : object,\n",
        "    input_channel: int = 0,\n",
        "    output_channel: int = None,\n",
        "    lines: bool = True,\n",
        "    figsize: Tuple[int, int] = (5, 5),\n",
        "    cmap: str = \"hot_r\",\n",
        "    color: str='r',\n",
        "    ) -> AxesImage:\n",
        "    # language=rst\n",
        "    \"\"\"\n",
        "    Plot a connection weight matrix of a :code:`Connection` with `locally connected\n",
        "    structure <http://yann.lecun.com/exdb/publis/pdf/gregor-nips-11.pdf>_.\n",
        "    :param lc: LC connection object of LCNet\n",
        "    :param input_channel: indicates weights which connected to this channel of input \n",
        "    :param output_channel: indicates weights of specific channel in the output layer\n",
        "    :param lines: Whether or not to draw horizontal and vertical lines separating input regions.\n",
        "    :param figsize: Horizontal, vertical figure size in inches.\n",
        "    :param cmap: Matplotlib colormap.\n",
        "    :return: Used for re-drawing the weights plot.\n",
        "    \"\"\"\n",
        "\n",
        "    n_sqrt = int(np.ceil(np.sqrt(lc.out_channels)))\n",
        "    sel_slice = lc.w.view(lc.in_channels, lc.out_channels, lc.conv_size[0], lc.conv_size[1], lc.kernel_size[0], lc.kernel_size[1]).cpu()\n",
        "    input_size = _pair(int(np.sqrt(lc.source.n)))\n",
        "    \n",
        "    if output_channel is None:\n",
        "        sel_slice = sel_slice[input_channel, ...]\n",
        "        reshaped = reshape_LC_weights(sel_slice, lc.out_channels, lc.kernel_size, lc.conv_size, input_size)\n",
        "    else:\n",
        "        sel_slice = sel_slice[input_channel, output_channel, ...]\n",
        "        sel_slice = sel_slice.unsqueeze(0)\n",
        "        reshaped = reshape_LC_weights(sel_slice, 1, lc.kernel_size, lc.conv_size, input_size)\n",
        "        print(reshaped.shape)\n",
        "\n",
        "    fig, ax = plt.subplots(figsize=figsize)\n",
        "\n",
        "    im = ax.imshow(reshaped.cpu(), cmap=cmap, vmin=lc.wmin, vmax=lc.wmax)\n",
        "    div = make_axes_locatable(ax)\n",
        "    cax = div.append_axes(\"right\", size=\"5%\", pad=0.05)\n",
        "\n",
        "    if lines and  output_channel is None:\n",
        "        for i in range(\n",
        "            n_sqrt * lc.kernel_size[0],\n",
        "            n_sqrt * lc.conv_size[0] * lc.kernel_size[0],\n",
        "            n_sqrt * lc.kernel_size[0],\n",
        "        ):\n",
        "            ax.axhline(i - 0.5, color=color, linestyle=\"--\")\n",
        "\n",
        "        for i in range(\n",
        "            n_sqrt * lc.kernel_size[1],\n",
        "            n_sqrt * lc.conv_size[1] * lc.kernel_size[1],\n",
        "            n_sqrt * lc.kernel_size[1],\n",
        "        ):\n",
        "            ax.axvline(i - 0.5, color=color, linestyle=\"--\")\n",
        "\n",
        "    ax.set_xticks(())\n",
        "    ax.set_yticks(())\n",
        "    ax.set_aspect(\"auto\")\n",
        "\n",
        "    plt.colorbar(im, cax=cax)\n",
        "    fig.tight_layout()\n",
        "\n",
        "    return im\n",
        "\n",
        "def plot_LC_weights(lc : object,\n",
        "    input_channel: int = 0,\n",
        "    output_channel: int = None,\n",
        "    lines: bool = True,\n",
        "    figsize: Tuple[int, int] = (5, 5),\n",
        "    cmap: str = \"hot_r\",\n",
        "    color: str='r',\n",
        "    ) -> AxesImage:\n",
        "    # language=rst\n",
        "    \"\"\"\n",
        "    Plot a connection weight matrix of a :code:`Connection` with `locally connected\n",
        "    structure <http://yann.lecun.com/exdb/publis/pdf/gregor-nips-11.pdf>_.\n",
        "    :param lc: LC connection object of LCNet\n",
        "    :param input_channel: indicates weights which connected to this channel of input \n",
        "    :param output_channel: indicates weights of specific channel in the output layer\n",
        "    :param lines: Whether or not to draw horizontal and vertical lines separating input regions.\n",
        "    :param figsize: Horizontal, vertical figure size in inches.\n",
        "    :param cmap: Matplotlib colormap.\n",
        "    :return: Used for re-drawing the weights plot.\n",
        "    \"\"\"\n",
        "\n",
        "    n_sqrt = int(np.ceil(np.sqrt(lc.out_channels)))\n",
        "    sel_slice = lc.w.view(lc.in_channels, lc.out_channels, lc.conv_size[0], lc.conv_size[1], lc.kernel_size[0], lc.kernel_size[1]).cpu()\n",
        "    input_size = _pair(int(np.sqrt(lc.source.n)))\n",
        "    \n",
        "    if output_channel is None:\n",
        "        sel_slice = sel_slice[input_channel, ...]\n",
        "        reshaped = reshape_LC_weights(sel_slice, lc.out_channels, lc.kernel_size, lc.conv_size, input_size)\n",
        "    else:\n",
        "        sel_slice = sel_slice[input_channel, output_channel, ...]\n",
        "        sel_slice = sel_slice.unsqueeze(0)\n",
        "        reshaped = reshape_LC_weights(sel_slice, 1, lc.kernel_size, lc.conv_size, input_size)\n",
        "        #print(reshaped.shape)\n",
        "\n",
        "    fig, ax = plt.subplots(figsize=figsize)\n",
        "\n",
        "    im = ax.imshow(reshaped.cpu(), cmap=cmap, vmin=lc.wmin, vmax=lc.wmax)\n",
        "    div = make_axes_locatable(ax)\n",
        "    cax = div.append_axes(\"right\", size=\"5%\", pad=0.05)\n",
        "\n",
        "    if lines and  output_channel is None:\n",
        "        for i in range(\n",
        "            lc.kernel_size[0],#n_sqrt * lc.kernel_size[0],\n",
        "            n_sqrt*lc.conv_size[0] * lc.kernel_size[0],#n_sqrt * lc.conv_size[0] * lc.kernel_size[0],\n",
        "            lc.kernel_size[0],#,n_sqrt * lc.kernel_size[0],\n",
        "        ):\n",
        "            #print(i)\n",
        "            ax.axhline(i, color=color, linestyle=\"--\")\n",
        "\n",
        "        for i in range(\n",
        "            lc.kernel_size[1],#n_sqrt * lc.kernel_size[1],\n",
        "            n_sqrt*lc.conv_size[1] * lc.kernel_size[1],#n_sqrt * lc.conv_size[1] * lc.kernel_size[1],\n",
        "            lc.kernel_size[1],#n_sqrt * lc.kernel_size[1],\n",
        "        ):\n",
        "            ax.axvline(i, color=color, linestyle=\"--\")\n",
        "            \n",
        "        for i in range(\n",
        "            n_sqrt * lc.kernel_size[0],\n",
        "            n_sqrt * lc.conv_size[0] * lc.kernel_size[0],\n",
        "            n_sqrt * lc.kernel_size[0],\n",
        "        ):\n",
        "            #print(i)\n",
        "            ax.axhline(i, color='b', linestyle=\"--\")\n",
        "\n",
        "        for i in range(\n",
        "            n_sqrt * lc.kernel_size[1],\n",
        "            n_sqrt * lc.conv_size[1] * lc.kernel_size[1],\n",
        "            n_sqrt * lc.kernel_size[1],\n",
        "        ):\n",
        "            ax.axvline(i, color='b', linestyle=\"--\")\n",
        "\n",
        "    ax.set_xticks(())\n",
        "    ax.set_yticks(())\n",
        "    ax.set_aspect(\"auto\")\n",
        "\n",
        "    plt.colorbar(im, cax=cax)\n",
        "    fig.tight_layout()\n",
        "\n",
        "    return im\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ywXyWP0I83Au"
      },
      "source": [
        "# Design network"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 79,
      "metadata": {
        "id": "PcU9FSsVi4Bw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c2c4f8c2-948c-445a-e6c7-f404b3fede9b"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33msingularbrain\u001b[0m (use `wandb login --relogin` to force relogin)\n"
          ]
        }
      ],
      "source": [
        "WANDB = True\n",
        "if WANDB:\n",
        "    !pip install -q wandb\n",
        "    !wandb login\n",
        "    import wandb"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 159,
      "metadata": {
        "id": "8bZpJmlrJDa9"
      },
      "outputs": [],
      "source": [
        "compute_size = lambda inp_size, k, s: int((inp_size-k)/s) + 1\n",
        "def convergence(c):\n",
        "    if c.norm is None:\n",
        "        return 1-torch.mean((c.w-c.wmin)*(c.wmax-c.w))/((c.wmax-c.wmin)/2)**2\n",
        "    else:\n",
        "        mean_norm_factor = c.norm / c.w.shape[-1]\n",
        "        return  1-(torch.mean((c.w-c.wmin)*(c.wmax-c.w))/((c.wmax-c.wmin)/2)**2)\n",
        "\n",
        "        \n",
        "class FCSNN(Network):\n",
        "    def __init__(\n",
        "        self,\n",
        "        neuron_per_action,\n",
        "        time,\n",
        "        reward_fn,\n",
        "        observation_period,\n",
        "        decision_period,\n",
        "        intensity,\n",
        "        classic_reward,\n",
        "        num_episodes,\n",
        "        max_steps,\n",
        "        nu,\n",
        "        update_rule,\n",
        "        inh_type,\n",
        "        inh_factor,\n",
        "        cartpole_online,\n",
        "        save_path=None,\n",
        "        load_path=None,\n",
        "        dt=1,\n",
        "        tc_trace=20,\n",
        "        trace_additive=False,\n",
        "        online=False,\n",
        "        wandb_active = False,\n",
        "        batch_size=1,\n",
        "        save_interval = 100,\n",
        "        wmin=0,\n",
        "        wmax=1,\n",
        "        clamp_intensity=None,\n",
        "        **kwargs,\n",
        "    ) -> None:\n",
        "        # language=rst\n",
        "        \"\"\"\n",
        "        Constructor for class ``FCSNN``.\n",
        "        \"\"\"\n",
        "        manual_seed(SEED)\n",
        "        super().__init__(dt=dt, reward_fn = None, online=online)\n",
        "        self.cartpole_online = cartpole_online\n",
        "        self.dt = dt\n",
        "        self.intensity = intensity\n",
        "        self.reward_fn = reward_fn\n",
        "        self.batch_size = batch_size\n",
        "        self.reward_fn.network = self\n",
        "        self.reward_fn.dt = self.dt\n",
        "        self.n_actions = 2\n",
        "        self.n_classes = 2\n",
        "        self.observation_period = observation_period,\n",
        "        self.decision_period = decision_period,\n",
        "        self.classic_reward = classic_reward\n",
        "        self.neuron_per_class = neuron_per_action\n",
        "        self.neuron_per_action = neuron_per_action\n",
        "        self.save_path = save_path\n",
        "        self.load_path = load_path\n",
        "        self.save_interval = save_interval\n",
        "        self.time = time\n",
        "        self.clamp_intensity = clamp_intensity\n",
        "        self.wmin = wmin \n",
        "        self.wmax = wmax\n",
        "        self.wandb_active = wandb_active\n",
        "        self.num_episodes = num_episodes\n",
        "        self.max_steps= max_steps\n",
        "        self.rew = 0.0\n",
        "        self.local_rewarding = kwargs.get('local_rewarding', None)\n",
        "        kwargs['target_name'] = None\n",
        "        self.env = gym.make('CartPole-v0')\n",
        "        self.env.reset()\n",
        "\n",
        "      \n",
        "        ### nodes\n",
        "        inp = Input(shape= [2], traces=True, tc_trace=tc_trace, traces_additive = trace_additive)\n",
        "        self.add_layer(inp, name=\"input\")\n",
        "\n",
        "        # main = LIFNodes(shape= [10], traces=True, tc_trace=tc_trace,\n",
        "        #                      traces_additive = trace_additive)\n",
        "        \n",
        "        # self.add_layer(main, name=\"main\")\n",
        "\n",
        "        out = LIFNodes(shape= [neuron_per_action*2], traces=True, tc_trace=tc_trace,\n",
        "                             traces_additive = trace_additive)\n",
        "\n",
        "        self.add_layer(out, name=\"output\")\n",
        "\n",
        "        ### connections \n",
        "        inp_main = Connection(inp, out, nu = _pair(nu), update_rule = update_rule, wmin = wmin, wmax= wmax)\n",
        "\n",
        "        #main_out = Connection(main, out, nu = _pair(nu), update_rule = update_rule, wmin = wmin, wmax= wmax)\n",
        "       \n",
        "        self.add_connection(inp_main, \"input\", \"output\")\n",
        "\n",
        "        # self.add_connection(main_out, \"main\", \"output\")\n",
        "\n",
        "        \n",
        "        ### Inhibitory:\n",
        "        if inh_type == 'between_layers':\n",
        "            w = -inh_factor * torch.ones(out.n, out.n)\n",
        "            for c in range(self.n_actions):\n",
        "                w[c, c] = 0\n",
        "            out_recurrent_inhibition = Connection(\n",
        "                source=out,\n",
        "                target=out,\n",
        "                w=w,\n",
        "                wmin=-inh_factor,\n",
        "                wmax=0,\n",
        "            )\n",
        "            self.add_connection(out_recurrent_inhibition, \"output\", \"output\")            \n",
        "        elif inh_type == None:\n",
        "            pass\n",
        "\n",
        "        # Directs network to GPU\n",
        "        if gpu:\n",
        "            self.to(\"cuda\")\n",
        "\n",
        "\n",
        "    def get_state_spiking(self,state):\n",
        "        intensity = self.intensity\n",
        "\n",
        "        s_norm = torch.tensor(([state[2]+self.env.theta_threshold_radians+0.05, state[3]*0.02+0.06])).type(torch.float32)\n",
        "        f1 = lambda x: x * self.intensity\n",
        "        a = f1(s_norm)\n",
        "        f2 = lambda x: PoissonEncoder(time=self.time, dt=self.dt)(x)\n",
        "        s_conv = f2(a)\n",
        "        return s_conv\n",
        "\n",
        "    def learn(\n",
        "        self,\n",
        "        hparams = None,\n",
        "        online_validate = True,\n",
        "        running_window_length = 250,\n",
        "        verbose = True,\n",
        "        **kwargs\n",
        "    ):\n",
        "        manual_seed(SEED)\n",
        "        if self.wandb_active:\n",
        "            wandb.watch(self)\n",
        "        self.verbose = verbose\n",
        "\n",
        "        reward_monitor = RewardMonitor(time =self.time)\n",
        "\n",
        "        self.add_monitor(reward_monitor, name=\"reward\")\n",
        "\n",
        "        reward_hist = []\n",
        "\n",
        "        self.spikes = {}\n",
        "        for layer in set(self.layers):\n",
        "            self.spikes[layer] = Monitor(self.layers[layer], state_vars=[\"s\"], time=None)\n",
        "            self.add_monitor(self.spikes[layer], name=\"%s_spikes\" % layer)\n",
        "            self.dopaminergic_layers = self.layers[\"output\"]\n",
        "       \n",
        "        self.episode = 0\n",
        "        rew = 0.0\n",
        "        tot_rew = 0.0\n",
        "\n",
        "\n",
        "        if self.load_path:\n",
        "            \n",
        "            self.model_params = torch.load(self.load_path)\n",
        "            self.load_state_dict(torch.load(self.load_path)['state_dict'])\n",
        "            self.episode =  self.model_params['episode']\n",
        "            hparams = self.model_params['hparams']\n",
        "            reward_hist = self.model_params['reward_hist']\n",
        "            print(f'Previous model loaded! Resuming training from episode {self.episode}...\\n')\n",
        "        else:\n",
        "            self.env = gym.make('CartPole-v0')\n",
        "            self.env.reset()\n",
        "            print(f'Previous model not found! Training from the beginning...\\n')\n",
        "\n",
        "        pbar = tqdm(total=self.num_episodes)\n",
        "        \n",
        "        kwargs['target_name'] = None\n",
        "        for ep in range(self.num_episodes):\n",
        "            # print(f\"episode: {ep+1}\")\n",
        "            self.reset_state_variables()\n",
        "            self.env.reset()\n",
        "            done = False\n",
        "            tot_rew = 0.0\n",
        "            success = False\n",
        "            failure = False\n",
        "            num_steps = 0\n",
        "            for t in count():\n",
        "                \n",
        "                if t != 0:\n",
        "                    print(\"state (x, x_dot, theta (rad), theta_dot):\", round(x,3), round(x_dot*0.02, 3), round(theta, 3), round(theta_dot*0.02,3), \"output\", sum_spikes, 'selected_action:',  selected_action, 'rew:', round(rew,3))\n",
        "                    \n",
        "                inp_spikes = self.get_state_spiking(self.env.state)\n",
        "                if gpu:\n",
        "                    inputs = {\"input\": inp_spikes.cuda().view(self.time, self.batch_size, 2)}\n",
        "                else:\n",
        "                    inputs = {\"input\": inp_spikes.view(self.time, self.batch_size, 2)}\n",
        "\n",
        "\n",
        "                clamp = {}\n",
        "                if self.clamp_intensity is not None:\n",
        "                    encoder = PoissonEncoder(time = self.time, dt = self.dt)\n",
        "                    clamp['output'] = encoder.enc(datum = torch.rand(self.layers['output'].n)*self.clamp_intensity,time = self.time, dt = self.dt)\n",
        "\n",
        "                # if done:\n",
        "                #     failure = True\n",
        "\n",
        "                if t >= self.max_steps:\n",
        "                    success = True\n",
        "                    done = True\n",
        "                elif done:\n",
        "                    failure = True\n",
        "\n",
        "\n",
        "                self.run(inputs=inputs, \n",
        "                        # time = self.time,\n",
        "                        one_step=False,\n",
        "                        clamp = clamp,\n",
        "                        env = self.env,\n",
        "                        success = success,\n",
        "                        failure = failure,\n",
        "                        **kwargs,\n",
        "                        )\n",
        "                \n",
        "                rew = float(reward_monitor.get()[0])\n",
        "                tot_rew += rew\n",
        "                \n",
        "                #main = self.spikes['main'].get('s')\n",
        "                out_spikes = self.spikes[\"output\"].get(\"s\").view(self.time, self.batch_size, self.n_actions, self.neuron_per_action)\n",
        "                sum_spikes = out_spikes.sum(0).sum(2)\n",
        "                selected_action = torch.argmax(sum_spikes, dim=1)\n",
        "\n",
        "                #self.spikes['main'].reset_state_variables()\n",
        "                self.spikes[\"output\"].reset_state_variables()\n",
        "                reward_monitor.reset_state_variables()\n",
        "                #self.reset_state_variables()\n",
        "\n",
        "                if done:\n",
        "                    if success == True:\n",
        "                        print(\"output\", sum_spikes, 'selected_action:',  selected_action, 'rew:', rew)\n",
        "                        print('\\Successful episode!')\n",
        "                        num_steps = t+1\n",
        "                    else:\n",
        "                        print(\"output\", sum_spikes, 'selected_action:',  selected_action, 'rew:', rew)\n",
        "                        print('\\nEpisode not successful!')\n",
        "                        num_steps = t+1\n",
        "                    break\n",
        "\n",
        "                obs, reward, done, _ = self.env.step(int(selected_action[0]))     \n",
        "                x = obs[0]\n",
        "                x_dot = obs[1]\n",
        "                theta = obs[2]\n",
        "                theta_dot = obs[3]\n",
        "\n",
        "                # Get voltage recording.\n",
        "                #main_voltage = main_monitor.get(\"v\")\n",
        "\n",
        "                #tensorboard.update(step= i)\n",
        "\n",
        "\n",
        "            \n",
        "\n",
        "            if self.wandb_active:\n",
        "                wandb.log({\n",
        "                        **{'reward': tot_rew},\n",
        "                        **{' to '.join(name) + ' std': c.w.std().item() for name, c in self.connections.items() if name[0]!=name[1]},\n",
        "                        #**{name + ' spikes': monitor.get('s').sum().item() for name, monitor in self.spikes.items()},\n",
        "                        **{' to '.join(name) + \" gradients\": wandb.Histogram(c.w.cpu()) for name, c in self.connections.items() if name[0]!=name[1]},\n",
        "                    },\n",
        "                    step = self.episode)\n",
        "\n",
        "\n",
        "            #self.reward_fn.update() \n",
        "            #Plot_et.plot()    \n",
        "            # self.reset_state_variables()  # Reset state variables.\n",
        "            \n",
        "            self.episode += 1\n",
        "            reward_hist.append(tot_rew)\n",
        "            print(f'\\nEpisode {self.episode} lasted for {num_steps} time steps with total reward of {tot_rew}\\n')\n",
        "            if self.episode % self.save_interval == 0 and self.save_path:\n",
        "                model_params = {'state_dict': self.state_dict(), 'hparams': network_hparams, 'episode': self.episode, 'reward_hist': reward_hist}\n",
        "                torch.save(model_params, self.save_path)\n",
        "                print(\"\\n Model saved!\\n\")\n",
        "\n",
        "            pbar.set_description_str(\"Episode: \"+str(self.episode)+ \", Number of steps: \" + str(num_steps) +\", Episode Total Reward: \" + \"{:.2f}\".format(tot_rew))\n",
        "            pbar.update()\n",
        "\n",
        "    \n",
        "    def single_trial(self):\n",
        "        self.reset_state_variables()\n",
        "        \n",
        "        image = self.get_state_spiking()\n",
        "\n",
        "        if gpu:\n",
        "            inputs = {\"input\": image.cuda().view(self.time, 1, self.in_channels, self.crop_size, self.crop_size)}\n",
        "        else:\n",
        "            inputs = {\"input\": image.view(self.time, 1, self.in_channels, self.crop_size, self.crop_size)}\n",
        "\n",
        "        clamp = {}\n",
        "        if self.clamp_intensity is not None:\n",
        "            encoder = PoissonEncoder(time = self.time, dt = self.dt)\n",
        "            clamp['output'] = encoder.enc(datum = torch.rand(self.layers['output'].n)*self.clamp_intensity,time = self.time, dt = self.dt)\n",
        "\n",
        "        self.run(inputs=inputs, \n",
        "                time=self.time, \n",
        "                one_step = False,\n",
        "                mode = 'RL',\n",
        "                env = 'CartPole'\n",
        "                )\n",
        "    "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kCqAFucAUDb8"
      },
      "source": [
        "# Set up hyper-parameters"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "WANDB = True\n",
        "time = 100\n",
        "intensity = 400\n",
        "neuron_per_action = 10\n",
        "\n",
        "network_hparams = {\n",
        "    'neuron_per_action': neuron_per_action,\n",
        "    'time': time,\n",
        "    'reward_fn': RLTasks('CartPole-v0'),\n",
        "    'observation_period': 1,\n",
        "    'decision_period': time,\n",
        "    'intensity': intensity,\n",
        "    'classic_reward': True,\n",
        "    'num_episodes': 10000,\n",
        "    'max_steps': 200,\n",
        "    'nu': 0.01,\n",
        "    'update_rule': MSTDPET,\n",
        "    'inh_type': None,\n",
        "    'inh_factor': 100,\n",
        "    'cartpole_online': True,\n",
        "    'save_path': '/content/drive/My Drive/LCNet/FCSNN_cartpole.pth',\n",
        "    'load_path': None,#'/content/drive/My Drive/LCNet/FCSNN_cartpole.pth',\n",
        "    'dt':1,\n",
        "    'tc_trace':20,\n",
        "    'trace_additive':False,\n",
        "    'online':False,\n",
        "    'wandb_active':WANDB,\n",
        "    'batch_size':1,\n",
        "    'save_interval':100,\n",
        "    'wmin':0,\n",
        "    'wmax':1,\n",
        "    'clamp_intensity':None,\n",
        "}"
      ],
      "metadata": {
        "id": "b4Neiuljhev7"
      },
      "execution_count": 160,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SokdidkrV2Z5"
      },
      "source": [
        "# Learning"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "if WANDB:\n",
        "    wandb.init(project='FCSNN_CartPole', entity='singularbrain', config=network_hparams)"
      ],
      "metadata": {
        "id": "WdEY4JihhdJg",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 177,
          "referenced_widgets": [
            "479b940d219c400293f9eca585255145",
            "a1ec63aa67a4434e9ba4c6918307cf13",
            "19243be799e34b24b6b32546ce58e61b",
            "15247ec281aa4b49a7d2b47a4807363d",
            "fd00a3aa43144582bd296a316162b670",
            "7afcac2f6c074f0eb83cb8fc764fe1f4",
            "bde27b34ffad481c9e3eb8e694d6dfea",
            "665a14eddb0a4e90b53f4edef99ef536"
          ]
        },
        "outputId": "519ec09c-3ad1-4bc8-a0c6-8ad7c14e93cd"
      },
      "execution_count": 161,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "Finishing last run (ID:1ebwyk26) before initializing another..."
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<br/>Waiting for W&B process to finish, PID 1937... <strong style=\"color:green\">(success).</strong>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "479b940d219c400293f9eca585255145",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "VBox(children=(Label(value=' 0.00MB of 0.00MB uploaded (0.00MB deduped)\\r'), FloatProgress(value=1.0, max=1.0)…"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<style>\n",
              "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: right }\n",
              "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; width: 100% }\n",
              "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
              "    </style>\n",
              "<div class=\"wandb-row\"><div class=\"wandb-col\">\n",
              "</div><div class=\"wandb-col\">\n",
              "</div></div>\n",
              "Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)\n",
              "<br/>Synced <strong style=\"color:#cdcd00\">legendary-monkey-18</strong>: <a href=\"https://wandb.ai/singularbrain/FCSNN_CartPole/runs/1ebwyk26\" target=\"_blank\">https://wandb.ai/singularbrain/FCSNN_CartPole/runs/1ebwyk26</a><br/>\n",
              "Find logs at: <code>./wandb/run-20220207_170909-1ebwyk26/logs</code><br/>\n"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "Successfully finished last run (ID:1ebwyk26). Initializing new run:<br/>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "                    Syncing run <strong><a href=\"https://wandb.ai/singularbrain/FCSNN_CartPole/runs/2ienjz4w\" target=\"_blank\">spring-water-19</a></strong> to <a href=\"https://wandb.ai/singularbrain/FCSNN_CartPole\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://docs.wandb.com/integrations/jupyter.html\" target=\"_blank\">docs</a>).<br/>\n",
              "\n",
              "                "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 162,
      "metadata": {
        "id": "Venb2KhSYrT_",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9524938f-6e76-42eb-a0c7-9da7612252c4"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "if network_hparams['save_path'] or network_hparams['load_path']:    \n",
        "    drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "oThYyYvHJzeP",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "dded64c55e254f3a8a29b6dbc601986d",
            "a9b56a1e2ab74ba5b21dbcab1864333c",
            "85c4a0efabd14d04ba038a0dc7bc4471",
            "96786d47e7464c2188f0ea57a22d296c",
            "bebbbeafab4e4a8787505c4bc44a677a",
            "093d8ed694a64650afa04ca10f791892",
            "944d9e6c5bcc4ad28cc1476ebe8511d3",
            "c412c2309350492193de78b84249870a",
            "1a6151f8bd2e432db233a9dc4d26ff70",
            "8bf6a911afc546df813d742070ac5d4f",
            "2b1c73cf247a4bdf8ac420da3fbc7270"
          ]
        },
        "outputId": "d51bb91c-7ef9-4718-a1f3-59e486967fc4"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Previous model not found! Training from the beginning...\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "dded64c55e254f3a8a29b6dbc601986d",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "  0%|          | 0/10000 [00:00<?, ?it/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1;30;43mStreaming output truncated to the last 5000 lines.\u001b[0m\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.028 0.003 0.04 -0.005 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.031 0.007 0.035 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.038 0.003 0.024 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.042 0.007 0.019 -0.011 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.049 0.003 0.008 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.053 -0.0 0.004 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.052 0.003 0.005 -0.004 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.055 -0.0 0.001 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.055 -0.004 0.002 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.051 -0.008 0.009 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.042 -0.012 0.022 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.03 -0.008 0.041 0.013 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.022 -0.004 0.055 0.008 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.017 -0.001 0.063 0.002 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.017 -0.004 0.065 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.012 -0.008 0.073 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.004 -0.004 0.088 0.009 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.001 -0.001 0.097 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.001 0.003 0.101 -0.001 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.002 0.007 0.1 -0.006 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.009 0.003 0.094 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.012 0.007 0.094 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.019 0.003 0.089 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.023 0.007 0.09 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.03 0.003 0.086 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.033 0.007 0.089 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.04 0.003 0.086 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.043 0.007 0.09 -0.002 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.05 0.011 0.088 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.06 0.015 0.081 -0.012 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.075 0.019 0.069 -0.018 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.094 0.015 0.051 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.108 0.019 0.04 -0.017 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.127 0.015 0.023 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.141 0.011 0.012 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.152 0.007 0.007 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.159 0.011 0.009 -0.005 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.17 0.007 0.004 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.176 0.003 0.005 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.179 -0.001 0.012 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.178 -0.005 0.025 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.173 -0.001 0.044 0.013 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.172 -0.005 0.058 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.167 -0.009 0.077 0.026 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.158 -0.005 0.103 0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.153 -0.001 0.123 0.015 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.152 0.003 0.138 0.01 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.155 0.007 0.148 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.162 0.003 0.153 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.164 0.007 0.165 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.171 0.01 0.172 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.181 0.014 0.174 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.195 0.018 0.172 -0.007 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.213 0.022 0.165 -0.012 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.235 0.026 0.153 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.261 0.03 0.137 -0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.291 0.033 0.115 -0.026 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.324 0.03 0.089 -0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.354 0.033 0.069 -0.025 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.387 0.03 0.045 -0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.417 0.026 0.026 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.442 0.022 0.013 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.464 0.018 0.007 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.482 0.014 0.006 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.496 0.018 0.011 -0.001 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.513 0.014 0.011 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.527 0.018 0.016 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.545 0.014 0.016 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.559 0.01 0.022 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.569 0.014 0.033 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.583 0.01 0.039 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.593 0.014 0.051 0.006 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.606 0.018 0.057 0.001 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.624 0.022 0.058 -0.005 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.646 0.018 0.053 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.663 0.022 0.054 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.685 0.018 0.05 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.703 0.022 0.053 -0.003 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.724 0.025 0.049 -0.009 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.75 0.029 0.04 -0.014 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.779 0.025 0.026 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.804 0.029 0.018 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.834 0.025 0.004 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.859 0.021 -0.005 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.881 0.018 -0.007 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.898 0.014 -0.003 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.912 0.01 0.006 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.922 0.014 0.022 0.009 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.935 0.01 0.031 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.945 0.006 0.047 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.951 0.01 0.068 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.961 0.014 0.084 0.011 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.974 0.018 0.095 0.005 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.992 0.021 0.1 0.0 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.013 0.025 0.1 -0.005 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.038 0.029 0.095 -0.01 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.068 0.033 0.084 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.101 0.029 0.069 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.13 0.033 0.059 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.163 0.029 0.045 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.192 0.025 0.036 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.217 0.021 0.034 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.238 0.017 0.038 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.255 0.021 0.048 0.004 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.276 0.025 0.052 -0.001 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.302 0.029 0.051 -0.007 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.331 0.025 0.044 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.356 0.029 0.043 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.385 0.025 0.037 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.41 0.021 0.037 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.431 0.025 0.043 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.456 0.021 0.043 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.477 0.025 0.05 0.001 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.502 0.029 0.051 -0.005 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.531 0.025 0.046 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.556 0.029 0.047 -0.004 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.584 0.025 0.043 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.609 0.021 0.046 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.63 0.025 0.054 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.655 0.021 0.056 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.676 0.025 0.065 0.003 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.701 0.029 0.069 -0.002 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.73 0.033 0.067 -0.007 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.763 0.037 0.059 -0.013 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.799 0.04 0.046 -0.018 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.839 0.036 0.028 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.876 0.033 0.016 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.908 0.029 0.01 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.937 0.033 0.009 -0.006 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.97 0.036 0.003 -0.012 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.006 0.033 -0.008 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.039 0.036 -0.014 -0.012 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.075 0.033 -0.026 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.108 0.029 -0.032 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.136 0.025 -0.033 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.161 0.021 -0.028 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.182 0.017 -0.017 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.199 0.013 -0.0 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.212 0.017 0.022 0.016 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.229 0.013 0.039 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.242 0.017 0.061 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.259 0.013 0.078 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.272 0.017 0.101 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.289 0.021 0.119 0.013 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.31 0.025 0.131 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.335 0.029 0.139 0.003 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.363 0.032 0.141 -0.002 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.396 0.036 0.139 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.432 0.032 0.132 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 84 lasted for 154 time steps with total reward of 153.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.028 -0.004 0.011 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.024 -0.008 0.017 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.016 -0.004 0.028 0.006 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.012 -0.008 0.034 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.004 -0.012 0.046 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.007 -0.008 0.064 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.015 -0.012 0.077 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.027 -0.008 0.096 0.013 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.035 -0.004 0.109 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.039 -0.008 0.117 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.047 -0.004 0.132 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.051 -0.0 0.141 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.052 -0.004 0.146 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.056 -0.0 0.157 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.056 0.004 0.164 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.053 -0.0 0.166 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.053 0.003 0.174 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.05 0.007 0.178 -0.001 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.042 0.011 0.177 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.031 0.015 0.171 -0.01 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.016 0.019 0.161 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.002 0.023 0.146 -0.02 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.025 0.027 0.126 -0.025 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.052 0.03 0.102 -0.03 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.082 0.026 0.072 -0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.108 0.03 0.049 -0.028 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.139 0.026 0.021 -0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.165 0.023 -0.001 -0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.188 0.019 -0.018 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.206 0.015 -0.028 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.221 0.011 -0.033 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.232 0.007 -0.032 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.239 0.003 -0.026 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.242 -0.001 -0.013 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.241 0.003 0.005 0.012 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.244 -0.001 0.017 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.243 0.003 0.034 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.246 -0.001 0.047 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.245 0.003 0.065 0.013 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.248 0.007 0.077 0.007 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.255 0.011 0.084 0.002 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.266 0.007 0.086 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.273 0.011 0.095 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.283 0.015 0.097 -0.002 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.298 0.018 0.095 -0.008 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.316 0.015 0.088 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.331 0.018 0.087 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.349 0.014 0.08 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.364 0.018 0.08 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.382 0.022 0.075 -0.011 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.405 0.026 0.064 -0.016 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.431 0.03 0.048 -0.021 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.461 0.026 0.027 -0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.487 0.022 0.011 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.509 0.018 0.002 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.527 0.014 -0.001 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.542 0.01 0.001 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.552 0.014 0.01 0.002 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.566 0.01 0.012 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.577 0.007 0.02 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.583 0.003 0.035 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.586 0.007 0.055 0.015 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.593 0.01 0.07 0.009 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.603 0.014 0.079 0.004 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.617 0.018 0.083 -0.002 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.636 0.022 0.081 -0.007 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.658 0.026 0.074 -0.012 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.684 0.03 0.062 -0.018 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.713 0.026 0.045 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.739 0.022 0.033 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.761 0.026 0.028 -0.011 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.787 0.022 0.017 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.809 0.018 0.013 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.827 0.014 0.014 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.841 0.018 0.021 0.001 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.86 0.022 0.022 -0.004 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.881 0.026 0.018 -0.01 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.907 0.022 0.008 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.929 0.018 0.004 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.947 0.022 0.005 -0.004 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.969 0.018 0.001 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.987 0.014 0.003 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.001 0.018 0.011 0.002 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.02 0.014 0.013 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.034 0.01 0.02 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.044 0.014 0.034 0.008 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.058 0.018 0.042 0.002 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.076 0.022 0.045 -0.003 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.098 0.026 0.041 -0.009 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.124 0.03 0.033 -0.014 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.153 0.026 0.018 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.179 0.03 0.01 -0.014 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.209 0.034 -0.004 -0.02 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.242 0.03 -0.024 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.272 0.026 -0.038 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.298 0.022 -0.046 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.32 0.018 -0.049 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.338 0.014 -0.046 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.352 0.01 -0.038 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.362 0.006 -0.024 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.368 0.002 -0.004 0.025 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.371 0.006 0.021 0.019 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.377 0.002 0.04 0.025 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.38 -0.001 0.065 0.031 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.378 0.002 0.097 0.026 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.381 0.006 0.123 0.021 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.387 0.01 0.144 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.397 0.014 0.159 0.011 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.411 0.018 0.17 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.429 0.014 0.176 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.443 0.018 0.189 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.46 0.022 0.198 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.482 0.025 0.201 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.508 0.029 0.201 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.537 0.033 0.195 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.57 0.037 0.186 -0.014 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.607 0.041 0.171 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.648 0.045 0.153 -0.023 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.692 0.048 0.129 -0.028 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.741 0.052 0.101 -0.033 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.793 0.048 0.068 -0.027 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.842 0.052 0.041 -0.032 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.894 0.048 0.009 -0.026 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.942 0.045 -0.018 -0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.987 0.041 -0.038 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.027 0.037 -0.052 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.064 0.033 -0.061 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.097 0.029 -0.064 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.126 0.025 -0.062 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.151 0.021 -0.055 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.172 0.017 -0.042 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.189 0.013 -0.023 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.203 0.017 0.001 0.018 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.22 0.013 0.019 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.233 0.009 0.043 0.03 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.243 0.013 0.072 0.024 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.256 0.017 0.097 0.019 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.274 0.021 0.116 0.014 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.295 0.025 0.129 0.009 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.32 0.029 0.138 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.349 0.033 0.142 -0.001 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.381 0.037 0.14 -0.006 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.418 0.04 0.134 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 85 lasted for 144 time steps with total reward of 143.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.007 -0.004 -0.015 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.011 -0.008 -0.009 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.019 -0.012 0.002 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.03 -0.008 0.02 0.011 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.038 -0.012 0.031 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.05 -0.016 0.049 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.066 -0.012 0.072 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.077 -0.016 0.09 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.093 -0.012 0.114 0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.105 -0.008 0.133 0.014 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.113 -0.004 0.147 0.009 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.117 -0.0 0.156 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.117 0.004 0.16 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.113 0.007 0.159 -0.005 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.106 0.011 0.154 -0.01 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.095 0.015 0.144 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.079 0.019 0.129 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.06 0.023 0.109 -0.025 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.037 0.027 0.084 -0.03 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.011 0.031 0.054 -0.035 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.02 0.027 0.018 -0.029 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.047 0.023 -0.011 -0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.07 0.019 -0.034 -0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.089 0.015 -0.052 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.104 0.011 -0.064 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.115 0.007 -0.07 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.122 0.003 -0.071 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.125 -0.0 -0.066 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.125 -0.004 -0.056 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.121 -0.008 -0.041 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.112 -0.012 -0.02 0.026 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.1 -0.016 0.006 0.032 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.084 -0.012 0.038 0.026 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.072 -0.008 0.065 0.021 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.064 -0.004 0.086 0.015 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.059 -0.0 0.101 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.059 -0.004 0.111 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.055 -0.001 0.127 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.054 0.003 0.139 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.057 0.007 0.145 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.064 0.011 0.146 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.075 0.007 0.143 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.083 0.011 0.146 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.094 0.015 0.144 -0.007 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.108 0.019 0.138 -0.011 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.127 0.023 0.127 -0.016 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.15 0.026 0.11 -0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.176 0.03 0.089 -0.026 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.206 0.034 0.063 -0.032 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.24 0.038 0.031 -0.037 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.278 0.034 -0.006 -0.031 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.312 0.03 -0.037 -0.025 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.343 0.026 -0.063 -0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.369 0.022 -0.082 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.391 0.019 -0.097 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.41 0.015 -0.106 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.425 0.011 -0.109 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.435 0.007 -0.108 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.442 0.003 -0.101 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.445 -0.001 -0.09 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.445 -0.005 -0.073 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.44 -0.009 -0.051 0.028 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.431 -0.012 -0.023 0.033 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.419 -0.009 0.01 0.027 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.41 -0.012 0.037 0.033 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.398 -0.016 0.07 0.039 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.382 -0.012 0.109 0.034 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.369 -0.009 0.143 0.028 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.361 -0.005 0.171 0.024 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.356 -0.001 0.195 0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.355 0.003 0.213 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 86 lasted for 72 time steps with total reward of 71.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.021 -0.003 0.032 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.025 -0.007 0.038 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.032 -0.003 0.051 0.007 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.035 0.0 0.058 0.002 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.035 0.004 0.06 -0.004 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.031 0.0 0.056 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.03 -0.004 0.058 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.034 0.0 0.067 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.034 -0.004 0.07 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.037 0.0 0.079 0.004 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.037 0.004 0.083 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.033 0.0 0.082 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.032 0.004 0.087 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.028 0.0 0.086 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.028 0.004 0.092 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.024 0.008 0.093 -0.005 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.016 0.012 0.088 -0.01 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.004 0.016 0.078 -0.015 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.011 0.02 0.063 -0.02 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.031 0.023 0.043 -0.026 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.055 0.02 0.017 -0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.074 0.023 -0.003 -0.025 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.098 0.02 -0.028 -0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.117 0.016 -0.048 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.133 0.012 -0.062 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.145 0.008 -0.07 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.152 0.004 -0.073 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.156 0.0 -0.071 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.157 -0.004 -0.063 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.153 -0.008 -0.05 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.145 -0.012 -0.031 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.134 -0.015 -0.007 0.03 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.118 -0.012 0.023 0.024 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.107 -0.008 0.047 0.018 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.099 -0.004 0.065 0.013 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.095 0.0 0.078 0.007 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.095 0.004 0.085 0.002 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.099 0.008 0.087 -0.003 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.107 0.012 0.084 -0.009 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.119 0.016 0.075 -0.014 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.135 0.02 0.061 -0.019 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.154 0.016 0.042 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.17 0.012 0.029 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.182 0.016 0.022 -0.013 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.197 0.012 0.009 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.209 0.008 0.002 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.217 0.012 0.002 -0.007 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.228 0.008 -0.005 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.236 0.004 -0.006 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.24 -0.0 -0.0 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.24 -0.004 0.01 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.236 -0.0 0.027 0.011 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.236 -0.004 0.038 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.232 -0.0 0.055 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.232 -0.004 0.067 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.228 -0.0 0.084 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.228 -0.004 0.096 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.224 -0.0 0.115 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.224 0.004 0.128 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.228 -0.0 0.136 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.228 0.004 0.151 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.231 0.008 0.161 0.005 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.239 0.011 0.166 0.0 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.25 0.015 0.166 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.265 0.019 0.162 -0.009 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.284 0.023 0.153 -0.014 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.307 0.027 0.139 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.334 0.031 0.12 -0.024 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.365 0.035 0.097 -0.029 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.399 0.031 0.068 -0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.43 0.034 0.046 -0.028 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.464 0.031 0.018 -0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.495 0.027 -0.003 -0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.521 0.023 -0.019 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.544 0.019 -0.029 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.563 0.015 -0.033 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.578 0.011 -0.031 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.589 0.007 -0.024 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.596 0.003 -0.011 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.599 -0.001 0.008 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.599 0.003 0.032 0.019 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.602 -0.001 0.051 0.025 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.601 0.003 0.076 0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.605 -0.001 0.095 0.025 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.604 0.003 0.12 0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.607 0.007 0.141 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.614 0.011 0.156 0.01 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.625 0.015 0.166 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.64 0.019 0.171 0.001 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.659 0.022 0.172 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.681 0.026 0.168 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.707 0.03 0.16 -0.013 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.738 0.034 0.146 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.772 0.038 0.128 -0.023 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.809 0.042 0.105 -0.028 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.851 0.046 0.078 -0.033 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.897 0.049 0.044 -0.038 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.946 0.046 0.006 -0.032 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.992 0.049 -0.026 -0.038 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.041 0.046 -0.064 -0.032 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.087 0.042 -0.097 -0.027 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.129 0.038 -0.124 -0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.167 0.034 -0.146 -0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.2 0.03 -0.162 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.231 0.026 -0.174 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.257 0.022 -0.181 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.279 0.019 -0.184 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.298 0.015 -0.182 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.313 0.011 -0.175 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.323 0.007 -0.164 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.33 0.003 -0.148 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.334 -0.001 -0.127 0.026 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.333 -0.005 -0.101 0.031 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.328 -0.008 -0.071 0.036 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.32 -0.012 -0.035 0.041 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.308 -0.016 0.006 0.047 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.292 -0.02 0.053 0.053 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.271 -0.016 0.106 0.047 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.255 -0.012 0.153 0.042 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.243 -0.008 0.195 0.037 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.234 -0.005 0.232 0.033 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 87 lasted for 122 time steps with total reward of 121.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.02 -0.004 -0.028 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.016 -0.008 -0.022 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.008 -0.012 -0.01 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.004 -0.016 0.008 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.02 -0.02 0.032 0.03 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.04 -0.016 0.062 0.024 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.056 -0.012 0.086 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.068 -0.016 0.104 0.025 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.084 -0.012 0.129 0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.096 -0.008 0.149 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.104 -0.004 0.163 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.108 -0.001 0.173 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.109 0.003 0.178 0.0 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.106 0.007 0.179 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.098 0.011 0.175 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.087 0.015 0.166 -0.013 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.073 0.019 0.152 -0.018 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.054 0.023 0.134 -0.023 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.031 0.026 0.111 -0.028 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.005 0.03 0.083 -0.033 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.026 0.034 0.05 -0.038 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.06 0.03 0.012 -0.032 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.09 0.026 -0.021 -0.026 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.116 0.022 -0.047 -0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.139 0.019 -0.068 -0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.157 0.015 -0.083 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.172 0.011 -0.092 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.183 0.007 -0.097 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.19 0.003 -0.096 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.193 -0.001 -0.09 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.192 -0.005 -0.078 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.188 -0.009 -0.062 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.179 -0.012 -0.04 0.027 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.167 -0.016 -0.012 0.033 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.15 -0.012 0.021 0.027 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.138 -0.016 0.048 0.033 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.122 -0.012 0.081 0.027 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.109 -0.016 0.108 0.034 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.093 -0.012 0.142 0.029 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.08 -0.009 0.171 0.024 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.072 -0.005 0.194 0.019 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.067 -0.001 0.214 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[0, 1]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 88 lasted for 43 time steps with total reward of 42.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.041 -0.003 -0.023 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.038 -0.007 -0.017 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.031 -0.011 -0.005 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.02 -0.007 0.012 0.012 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.013 -0.003 0.024 0.006 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.01 0.001 0.03 0.0 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.011 -0.003 0.03 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.008 0.001 0.036 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.008 -0.003 0.037 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.005 -0.007 0.043 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.002 -0.003 0.056 0.007 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
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            "state (x, x_dot, theta (rad), theta_dot): 1.246 0.027 0.065 -0.013 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.273 0.023 0.052 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
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            "state (x, x_dot, theta (rad), theta_dot): 1.323 0.023 0.033 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.346 0.019 0.027 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.365 0.023 0.027 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.388 0.019 0.021 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.407 0.023 0.022 -0.005 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.43 0.019 0.016 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.449 0.015 0.017 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.464 0.019 0.023 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.483 0.015 0.024 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.498 0.011 0.031 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.509 0.007 0.044 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.516 0.011 0.063 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.528 0.007 0.076 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.535 0.011 0.096 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.546 0.015 0.11 0.009 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.561 0.019 0.119 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.58 0.023 0.123 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.603 0.019 0.121 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.621 0.023 0.127 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.644 0.027 0.127 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.671 0.03 0.122 -0.01 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.701 0.034 0.113 -0.015 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.735 0.038 0.098 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.774 0.034 0.078 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.808 0.038 0.065 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.846 0.034 0.046 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.88 0.03 0.033 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.91 0.034 0.027 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.944 0.03 0.015 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.975 0.026 0.009 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.001 0.03 0.009 -0.006 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.031 0.026 0.003 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.058 0.03 0.003 -0.006 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.088 0.034 -0.003 -0.012 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.122 0.03 -0.014 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.152 0.026 -0.02 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.179 0.03 -0.02 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.209 0.026 -0.026 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.235 0.022 -0.026 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.258 0.019 -0.021 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.276 0.015 -0.01 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.291 0.011 0.007 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.302 0.015 0.03 0.017 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.316 0.019 0.046 0.011 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.335 0.022 0.058 0.006 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.357 0.019 0.063 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.376 0.022 0.075 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.398 0.018 0.081 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.417 0.022 0.094 0.007 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[0, 1]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 89 lasted for 175 time steps with total reward of 174.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.026 -0.004 0.033 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.03 -0.001 0.039 0.0 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.031 0.003 0.04 -0.005 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.027 0.007 0.034 -0.011 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.02 0.011 0.024 -0.016 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.009 0.007 0.007 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.002 0.011 -0.003 -0.016 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.009 0.007 -0.019 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.016 0.003 -0.03 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.02 -0.001 -0.035 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.019 -0.004 -0.034 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.015 -0.008 -0.027 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.006 -0.012 -0.015 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.006 -0.016 0.003 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.022 -0.012 0.027 0.018 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.034 -0.008 0.045 0.012 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.043 -0.004 0.057 0.007 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.047 -0.001 0.064 0.001 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.048 0.003 0.065 -0.004 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.044 0.007 0.06 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.037 0.003 0.051 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.034 0.007 0.047 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.027 0.003 0.038 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.024 0.007 0.035 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.017 0.003 0.027 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.013 -0.001 0.024 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.014 0.003 0.028 -0.002 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.011 0.007 0.026 -0.008 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.004 0.011 0.018 -0.013 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.007 0.007 0.005 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.014 0.011 -0.003 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.025 0.007 -0.016 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.032 0.003 -0.024 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.036 -0.001 -0.026 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.035 -0.005 -0.022 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.03 -0.009 -0.012 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.022 -0.012 0.003 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.009 -0.009 0.024 0.015 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.001 -0.012 0.04 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.012 -0.009 0.061 0.016 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.02 -0.005 0.077 0.01 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.025 -0.001 0.087 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.025 -0.005 0.092 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.03 -0.001 0.103 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.031 -0.005 0.109 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.036 -0.001 0.122 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.037 0.003 0.129 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.034 0.007 0.131 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.027 0.011 0.129 -0.008 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.016 0.015 0.121 -0.013 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.001 0.018 0.109 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.017 0.015 0.091 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.032 0.018 0.08 -0.016 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.05 0.022 0.063 -0.022 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.072 0.026 0.042 -0.027 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.098 0.022 0.014 -0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.121 0.018 -0.007 -0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.139 0.014 -0.022 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.153 0.011 -0.031 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.164 0.007 -0.035 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.171 0.003 -0.033 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.173 -0.001 -0.025 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.172 -0.005 -0.012 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.167 -0.001 0.007 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.166 -0.005 0.02 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.161 -0.001 0.039 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.16 -0.005 0.052 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.155 -0.001 0.072 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.154 0.003 0.086 0.008 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.156 -0.001 0.094 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.155 0.003 0.109 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.158 -0.001 0.118 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.157 0.003 0.135 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.159 0.006 0.146 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.166 0.01 0.152 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.176 0.006 0.153 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.182 0.01 0.161 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.193 0.014 0.164 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.207 0.018 0.162 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.225 0.014 0.156 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.239 0.018 0.156 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.256 0.022 0.152 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.278 0.026 0.142 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.304 0.022 0.128 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.325 0.025 0.121 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.351 0.022 0.109 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.372 0.025 0.103 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.398 0.029 0.092 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.427 0.025 0.076 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.452 0.029 0.066 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.482 0.025 0.051 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.507 0.029 0.043 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.536 0.025 0.028 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.562 0.021 0.02 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.583 0.017 0.018 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.6 0.021 0.022 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.622 0.017 0.02 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.639 0.014 0.024 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.653 0.017 0.034 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.67 0.014 0.038 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.684 0.01 0.049 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.693 0.014 0.065 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.707 0.01 0.076 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.717 0.013 0.093 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.73 0.017 0.105 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.747 0.021 0.112 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.769 0.025 0.113 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.794 0.029 0.11 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.823 0.025 0.101 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.848 0.029 0.099 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.877 0.033 0.091 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.909 0.029 0.079 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.938 0.033 0.072 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.971 0.029 0.061 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.0 0.033 0.056 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.032 0.029 0.045 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.061 0.025 0.04 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.086 0.021 0.042 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.107 0.025 0.05 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.132 0.021 0.052 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.153 0.025 0.06 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.177 0.021 0.063 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.198 0.017 0.072 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.215 0.021 0.087 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.236 0.025 0.097 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.261 0.029 0.102 -0.001 output tensor([[6, 7]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.289 0.032 0.101 -0.006 output tensor([[0, 1]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.322 0.029 0.095 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.35 0.032 0.096 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.383 0.028 0.091 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.411 0.032 0.093 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.444 0.028 0.089 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.472 0.032 0.092 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.504 0.036 0.09 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.541 0.032 0.083 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.573 0.036 0.082 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.609 0.04 0.075 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.649 0.036 0.063 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.685 0.032 0.058 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.717 0.036 0.059 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.753 0.032 0.054 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.785 0.036 0.055 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.821 0.032 0.052 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.853 0.028 0.054 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.882 0.032 0.062 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.914 0.028 0.065 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.942 0.032 0.074 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.974 0.028 0.078 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.002 0.032 0.088 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.034 0.028 0.092 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.062 0.032 0.103 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.094 0.036 0.109 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.13 0.04 0.11 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.169 0.036 0.105 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.205 0.04 0.107 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.245 0.036 0.104 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.281 0.04 0.107 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.32 0.043 0.106 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.363 0.047 0.099 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.411 0.043 0.086 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 90 lasted for 161 time steps with total reward of 160.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.025 -0.003 -0.02 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.022 -0.007 -0.015 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.015 -0.011 -0.003 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.004 -0.007 0.014 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.003 -0.011 0.025 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.014 -0.015 0.042 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.028 -0.011 0.065 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.039 -0.015 0.083 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.054 -0.011 0.106 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.065 -0.007 0.125 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.072 -0.003 0.138 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.075 -0.007 0.147 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.082 -0.003 0.162 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.085 0.001 0.172 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.084 0.004 0.177 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.08 0.001 0.178 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.079 0.004 0.185 0.003 output tensor([[12, 16]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.075 0.0 0.188 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.075 0.004 0.198 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.07 0.008 0.203 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.062 0.012 0.204 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.05 0.016 0.2 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.034 0.012 0.192 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.023 0.016 0.191 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.007 0.02 0.185 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.013 0.023 0.175 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.036 0.027 0.16 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.063 0.023 0.141 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.087 0.027 0.128 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.114 0.031 0.11 -0.023 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.145 0.027 0.088 -0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.172 0.031 0.071 -0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.203 0.027 0.05 -0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.23 0.031 0.035 -0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.261 0.027 0.014 -0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.288 0.031 -0.0 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.319 0.027 -0.021 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.346 0.023 -0.035 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.369 0.019 -0.044 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.388 0.015 -0.047 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.403 0.011 -0.045 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.415 0.008 -0.037 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.422 0.004 -0.023 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.426 -0.0 -0.004 0.025 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.426 0.004 0.021 0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.429 -0.0 0.04 0.025 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.429 -0.004 0.065 0.031 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.425 -0.0 0.096 0.026 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.425 -0.004 0.122 0.032 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.421 -0.0 0.154 0.027 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.42 0.004 0.181 0.022 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.424 -0.0 0.203 0.029 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.423 0.003 0.232 0.025 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 91 lasted for 54 time steps with total reward of 53.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.013 -0.004 0.01 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.01 -0.008 0.016 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.002 -0.004 0.029 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.002 -0.008 0.036 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.009 -0.011 0.048 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.021 -0.008 0.067 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.028 -0.012 0.08 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.04 -0.008 0.1 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.048 -0.012 0.114 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.059 -0.008 0.135 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.067 -0.004 0.15 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.071 0.0 0.161 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.071 0.004 0.167 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.067 0.008 0.168 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.059 0.004 0.164 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.055 0.008 0.167 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.048 0.011 0.166 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.036 0.015 0.159 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.021 0.011 0.148 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.01 0.015 0.144 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.006 0.019 0.135 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.025 0.023 0.121 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.048 0.019 0.102 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.067 0.023 0.09 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.09 0.019 0.072 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.108 0.023 0.061 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.131 0.019 0.044 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.15 0.023 0.034 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.173 0.019 0.018 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.192 0.015 0.008 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.207 0.019 0.004 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.226 0.015 -0.005 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.241 0.011 -0.009 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.252 0.007 -0.007 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.259 0.003 0.001 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.262 0.007 0.014 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.27 0.003 0.022 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.273 0.007 0.036 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.28 0.003 0.044 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.283 -0.001 0.058 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.283 0.003 0.078 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.286 0.007 0.093 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.293 0.003 0.102 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.296 0.007 0.118 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.303 0.003 0.128 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.306 0.007 0.145 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.313 0.011 0.158 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.324 0.015 0.165 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.339 0.019 0.167 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.357 0.022 0.165 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.38 0.018 0.158 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.398 0.022 0.158 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.421 0.026 0.153 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.447 0.022 0.143 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.469 0.026 0.14 -0.008 output tensor([[12, 16]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.495 0.022 0.133 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.517 0.026 0.131 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.543 0.03 0.125 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.573 0.026 0.114 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.599 0.03 0.11 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.629 0.026 0.1 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.655 0.03 0.097 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.684 0.026 0.089 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.71 0.03 0.087 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.74 0.026 0.079 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.766 0.03 0.079 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.795 0.026 0.073 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.821 0.03 0.073 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.851 0.026 0.068 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.876 0.03 0.069 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.906 0.026 0.065 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.932 0.03 0.066 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.961 0.033 0.063 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.994 0.029 0.054 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.024 0.026 0.052 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.05 0.029 0.055 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.079 0.026 0.053 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.104 0.022 0.057 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.126 0.026 0.068 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.152 0.029 0.073 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.181 0.025 0.072 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.206 0.029 0.078 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.236 0.025 0.079 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.261 0.021 0.085 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.283 0.025 0.098 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.308 0.021 0.106 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.33 0.025 0.12 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.355 0.029 0.13 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.384 0.025 0.134 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.409 0.029 0.144 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.438 0.033 0.15 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.471 0.037 0.151 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.508 0.041 0.147 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.549 0.045 0.138 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.593 0.041 0.124 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.634 0.044 0.117 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.678 0.048 0.105 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.727 0.052 0.088 -0.022 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.779 0.048 0.065 -0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.827 0.052 0.05 -0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.879 0.048 0.028 -0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.928 0.044 0.013 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.972 0.04 0.004 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.012 0.044 0.001 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.057 0.04 -0.009 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.097 0.037 -0.012 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.134 0.033 -0.009 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.166 0.029 -0.001 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.195 0.025 0.013 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.22 0.029 0.033 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.248 0.025 0.048 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.273 0.029 0.068 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.302 0.033 0.083 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.335 0.036 0.092 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.371 0.033 0.096 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.404 0.036 0.106 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 92 lasted for 117 time steps with total reward of 116.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.04 -0.004 -0.008 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.035 -0.008 -0.001 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.027 -0.004 0.011 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.023 -0.008 0.017 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.014 -0.004 0.029 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.01 -0.008 0.035 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.001 -0.004 0.048 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.003 -0.008 0.054 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.012 -0.012 0.067 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.024 -0.008 0.086 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.032 -0.005 0.1 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.037 -0.008 0.108 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.045 -0.005 0.123 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.05 -0.001 0.133 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.051 -0.005 0.138 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.056 -0.001 0.149 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.056 0.003 0.155 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.053 0.007 0.157 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.047 0.003 0.154 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.044 0.007 0.157 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.037 0.011 0.156 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.026 0.014 0.15 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.012 0.018 0.139 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.007 0.014 0.123 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.021 0.018 0.114 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.039 0.014 0.1 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.054 0.018 0.092 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.072 0.014 0.079 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.086 0.018 0.073 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.104 0.014 0.061 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.119 0.018 0.056 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.137 0.014 0.045 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.151 0.018 0.04 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.169 0.014 0.03 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.183 0.01 0.026 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.193 0.006 0.028 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.2 0.002 0.036 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.202 0.006 0.05 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.209 0.002 0.058 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.211 0.006 0.073 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.217 0.01 0.082 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.228 0.006 0.085 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.234 0.01 0.095 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.244 0.014 0.1 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.258 0.01 0.099 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.268 0.014 0.105 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.282 0.01 0.106 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.292 0.014 0.113 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.306 0.01 0.115 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.316 0.014 0.124 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.33 0.018 0.127 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.347 0.022 0.126 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.369 0.018 0.119 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.387 0.021 0.119 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.408 0.025 0.114 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.434 0.021 0.104 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.455 0.025 0.101 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.48 0.021 0.092 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.502 0.025 0.09 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.527 0.021 0.082 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.548 0.025 0.081 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.573 0.021 0.075 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.595 0.025 0.075 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.62 0.021 0.069 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.641 0.017 0.07 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.658 0.021 0.077 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.68 0.017 0.079 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.697 0.021 0.087 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.718 0.025 0.09 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.743 0.021 0.087 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.764 0.025 0.091 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.789 0.021 0.09 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.81 0.025 0.094 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.835 0.021 0.094 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.856 0.025 0.1 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.881 0.029 0.101 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.91 0.025 0.097 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.934 0.029 0.099 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.963 0.025 0.096 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.988 0.029 0.099 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.016 0.032 0.097 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.049 0.029 0.09 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.078 0.032 0.09 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.11 0.029 0.084 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.139 0.032 0.085 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.171 0.028 0.08 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.199 0.025 0.081 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.224 0.028 0.089 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.252 0.025 0.092 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.277 0.028 0.101 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.305 0.024 0.105 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.33 0.028 0.115 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.358 0.032 0.12 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.39 0.036 0.12 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.426 0.032 0.115 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.458 0.036 0.116 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.494 0.04 0.113 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.534 0.036 0.104 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.57 0.04 0.102 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.61 0.044 0.094 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.654 0.04 0.082 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.693 0.044 0.076 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.737 0.04 0.064 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.777 0.044 0.059 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.82 0.04 0.049 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.86 0.044 0.044 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.903 0.04 0.035 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.943 0.036 0.031 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.979 0.04 0.033 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.018 0.036 0.03 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.054 0.04 0.033 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.094 0.036 0.03 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.129 0.04 0.033 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.169 0.036 0.03 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.204 0.032 0.034 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.236 0.036 0.043 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.272 0.032 0.047 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.304 0.036 0.057 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.339 0.039 0.062 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.379 0.036 0.061 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.414 0.039 0.066 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[0, 0]]) selected_action: tensor([0]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 93 lasted for 122 time steps with total reward of 121.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.024 -0.004 0.012 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.028 -0.008 0.017 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.036 -0.004 0.029 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.04 -0.008 0.035 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.047 -0.012 0.047 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.059 -0.008 0.065 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.067 -0.012 0.077 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.078 -0.008 0.096 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.086 -0.012 0.109 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.098 -0.008 0.129 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.105 -0.004 0.144 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.109 -0.0 0.154 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.109 0.004 0.158 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.106 -0.0 0.158 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.106 0.004 0.165 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.102 0.008 0.167 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.095 0.011 0.164 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.083 0.015 0.157 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.068 0.019 0.145 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.049 0.015 0.128 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.034 0.019 0.117 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.015 0.015 0.102 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.0 0.019 0.093 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.019 0.015 0.079 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.034 0.019 0.072 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.053 0.015 0.059 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.068 0.019 0.053 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.087 0.015 0.041 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.102 0.011 0.035 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.113 0.015 0.035 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.128 0.011 0.03 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.139 0.015 0.03 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.154 0.011 0.025 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.165 0.007 0.026 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.172 0.011 0.033 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.183 0.007 0.035 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.19 0.011 0.042 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.201 0.007 0.044 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.208 0.011 0.052 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.219 0.007 0.054 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.226 0.011 0.063 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.237 0.007 0.066 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.244 0.011 0.075 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.254 0.015 0.079 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.269 0.011 0.078 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.28 0.015 0.082 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.295 0.019 0.082 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.313 0.015 0.076 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.328 0.019 0.077 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.346 0.015 0.072 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.361 0.018 0.073 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.379 0.022 0.069 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.402 0.018 0.06 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.42 0.022 0.057 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.443 0.018 0.048 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.461 0.022 0.046 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.483 0.018 0.038 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.502 0.022 0.037 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.524 0.018 0.029 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.542 0.014 0.028 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.557 0.018 0.033 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.575 0.014 0.032 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.59 0.011 0.037 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.6 0.014 0.049 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.615 0.011 0.054 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.625 0.014 0.066 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.639 0.018 0.072 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.658 0.014 0.073 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.672 0.01 0.08 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.682 0.014 0.094 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.697 0.018 0.102 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.715 0.014 0.105 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.729 0.018 0.114 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.747 0.022 0.118 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.769 0.018 0.118 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.787 0.022 0.123 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.809 0.026 0.124 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.835 0.022 0.119 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.857 0.026 0.122 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.883 0.03 0.119 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.912 0.026 0.111 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.938 0.03 0.109 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.967 0.026 0.103 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.993 0.029 0.103 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.022 0.026 0.098 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.048 0.029 0.099 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.077 0.025 0.095 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.103 0.029 0.098 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.132 0.033 0.095 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.165 0.029 0.087 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.195 0.033 0.086 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.228 0.029 0.079 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.257 0.033 0.078 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.29 0.037 0.073 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.327 0.033 0.062 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.36 0.029 0.057 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.389 0.033 0.058 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.422 0.029 0.054 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.452 0.033 0.056 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.485 0.029 0.053 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.514 0.033 0.056 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.547 0.029 0.053 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.576 0.033 0.057 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.609 0.029 0.055 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.638 0.025 0.059 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.663 0.029 0.07 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.692 0.025 0.074 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.717 0.029 0.086 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.746 0.033 0.092 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.779 0.029 0.092 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.808 0.033 0.099 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.84 0.037 0.101 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.877 0.033 0.097 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.91 0.037 0.1 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.946 0.033 0.098 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.979 0.037 0.103 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.015 0.04 0.102 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.056 0.036 0.095 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.092 0.04 0.096 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.133 0.044 0.091 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.177 0.04 0.081 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.217 0.044 0.077 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.261 0.04 0.068 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.302 0.044 0.065 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.346 0.04 0.057 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.386 0.044 0.055 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.43 0.04 0.048 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 94 lasted for 128 time steps with total reward of 127.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.01 -0.003 0.048 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.013 -0.007 0.054 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.02 -0.003 0.066 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.024 -0.007 0.072 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.031 -0.003 0.085 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.034 -0.007 0.092 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.041 -0.003 0.106 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.045 0.001 0.114 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.044 -0.003 0.118 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.047 0.0 0.127 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.047 0.004 0.132 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.043 0.008 0.132 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.034 0.012 0.126 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.022 0.008 0.116 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.014 0.012 0.113 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.002 0.016 0.104 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.014 0.012 0.09 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.026 0.016 0.083 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.041 0.02 0.07 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.061 0.016 0.052 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.077 0.02 0.04 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.096 0.016 0.023 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.112 0.02 0.012 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.132 0.016 -0.005 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.148 0.012 -0.016 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.159 0.008 -0.021 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.167 0.004 -0.02 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.171 0.0 -0.013 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.171 -0.004 -0.001 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.168 -0.008 0.017 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.16 -0.004 0.04 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.156 -0.008 0.059 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.149 -0.004 0.083 0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.145 -0.008 0.101 0.025 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.137 -0.004 0.126 0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.133 0.0 0.146 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.133 0.004 0.161 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.137 0.008 0.171 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.145 0.012 0.176 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.156 0.008 0.177 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.164 0.011 0.184 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.175 0.015 0.187 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.191 0.019 0.185 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.21 0.015 0.178 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.225 0.019 0.179 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.244 0.023 0.175 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.267 0.027 0.166 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.294 0.031 0.152 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.324 0.027 0.134 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.351 0.031 0.123 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.382 0.027 0.106 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.408 0.03 0.097 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.439 0.027 0.082 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.465 0.03 0.073 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.496 0.026 0.059 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.522 0.03 0.052 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.552 0.026 0.039 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.579 0.023 0.032 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.601 0.019 0.031 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.62 0.023 0.036 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.643 0.019 0.036 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.661 0.023 0.042 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.684 0.026 0.042 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.71 0.022 0.036 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.733 0.019 0.037 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.751 0.022 0.043 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.774 0.019 0.045 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.792 0.022 0.052 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.815 0.019 0.053 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.833 0.022 0.061 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.856 0.026 0.063 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.882 0.022 0.06 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.904 0.026 0.063 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.93 0.022 0.061 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.953 0.026 0.065 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.979 0.022 0.063 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.001 0.026 0.068 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.028 0.022 0.067 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.05 0.026 0.072 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.076 0.022 0.073 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.098 0.026 0.079 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.124 0.022 0.08 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.146 0.026 0.087 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.172 0.03 0.089 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.202 0.026 0.086 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.228 0.03 0.089 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.258 0.034 0.087 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.292 0.03 0.079 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.322 0.034 0.078 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.356 0.03 0.072 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.385 0.034 0.071 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.419 0.038 0.066 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.457 0.034 0.055 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.49 0.038 0.05 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.528 0.034 0.04 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.561 0.037 0.036 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.599 0.034 0.027 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.632 0.037 0.023 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.67 0.034 0.014 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.703 0.037 0.011 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.741 0.034 0.002 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.774 0.03 -0.001 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.804 0.026 0.002 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.83 0.022 0.01 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.852 0.026 0.025 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.877 0.022 0.034 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.899 0.026 0.048 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.925 0.022 0.058 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.947 0.026 0.073 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.973 0.022 0.083 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.994 0.026 0.099 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.02 0.03 0.11 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.05 0.033 0.115 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.083 0.029 0.116 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.112 0.033 0.123 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.146 0.037 0.125 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.183 0.033 0.121 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.216 0.037 0.125 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.253 0.041 0.123 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.294 0.037 0.117 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.331 0.041 0.117 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.372 0.045 0.112 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.417 0.041 0.101 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 95 lasted for 124 time steps with total reward of 123.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.016 -0.004 0.021 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.02 -0.008 0.027 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.028 -0.004 0.038 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.031 -0.008 0.045 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.039 -0.012 0.057 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.051 -0.008 0.076 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.058 -0.012 0.089 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.07 -0.008 0.108 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.078 -0.004 0.122 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.081 -0.008 0.131 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.089 -0.004 0.146 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.093 -0.0 0.157 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.093 -0.004 0.162 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.097 -0.0 0.175 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.097 0.004 0.182 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.093 0.008 0.185 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.086 0.011 0.184 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.074 0.007 0.178 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.067 0.011 0.178 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.056 0.015 0.174 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.041 0.019 0.166 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.022 0.015 0.152 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.007 0.019 0.146 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.012 0.015 0.135 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.027 0.019 0.13 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.046 0.023 0.121 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.069 0.027 0.106 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.095 0.023 0.087 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.118 0.027 0.074 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.145 0.023 0.055 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.167 0.026 0.043 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.194 0.023 0.026 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.216 0.019 0.014 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.235 0.023 0.009 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.257 0.019 -0.002 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.276 0.015 -0.008 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.291 0.011 -0.007 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.302 0.015 -0.001 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.316 0.011 -0.0 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.327 0.007 0.006 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.334 0.011 0.018 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.345 0.007 0.025 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.352 0.003 0.037 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.355 0.007 0.055 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.362 0.011 0.068 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.373 0.007 0.075 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.379 0.011 0.089 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.39 0.007 0.097 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.397 0.003 0.111 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.4 0.007 0.132 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.407 0.011 0.148 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.417 0.014 0.159 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.432 0.018 0.165 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.45 0.022 0.166 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.472 0.026 0.163 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.498 0.03 0.154 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.528 0.034 0.141 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.562 0.03 0.124 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.592 0.034 0.113 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.625 0.038 0.096 -0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.663 0.034 0.075 -0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.697 0.037 0.06 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.734 0.034 0.04 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.768 0.037 0.026 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.805 0.034 0.007 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.839 0.03 -0.007 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.868 0.026 -0.014 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.894 0.022 -0.016 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.916 0.018 -0.012 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.934 0.022 -0.003 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.956 0.018 0.001 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.974 0.014 0.011 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.988 0.01 0.026 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.998 0.014 0.047 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.012 0.01 0.063 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.022 0.014 0.085 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.036 0.01 0.101 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.046 0.014 0.124 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.06 0.01 0.142 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.07 0.014 0.166 0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.084 0.018 0.185 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.102 0.022 0.2 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.124 0.025 0.209 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 96 lasted for 84 time steps with total reward of 83.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.034 -0.004 0.007 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.03 -0.008 0.013 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.022 -0.004 0.026 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.018 -0.008 0.032 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.01 -0.012 0.045 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.002 -0.008 0.064 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.01 -0.004 0.077 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.015 -0.008 0.084 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.023 -0.004 0.098 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.027 -0.0 0.107 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.027 -0.004 0.11 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.032 -0.0 0.12 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.032 -0.004 0.125 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.036 -0.001 0.137 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.037 0.003 0.143 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.034 0.007 0.145 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.026 0.003 0.141 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.023 0.007 0.144 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.016 0.011 0.143 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.005 0.015 0.136 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.01 0.019 0.125 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.028 0.015 0.108 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.043 0.019 0.099 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.062 0.023 0.084 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.084 0.019 0.064 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.103 0.022 0.05 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.125 0.019 0.031 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.144 0.015 0.018 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.159 0.019 0.011 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.177 0.015 -0.002 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.192 0.011 -0.009 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.203 0.015 -0.01 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.217 0.011 -0.016 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.228 0.007 -0.018 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.235 0.003 -0.013 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.238 -0.001 -0.002 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.237 0.003 0.014 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.24 -0.001 0.024 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.239 0.003 0.04 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.242 -0.001 0.051 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.241 0.003 0.068 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.244 -0.001 0.079 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.243 0.003 0.096 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.245 0.007 0.108 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.252 0.003 0.115 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.255 0.007 0.129 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.262 0.011 0.137 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.272 0.007 0.14 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.279 0.01 0.15 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.289 0.014 0.155 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.304 0.018 0.155 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.322 0.022 0.151 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.344 0.026 0.141 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.37 0.022 0.127 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.392 0.026 0.119 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.417 0.022 0.107 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.439 0.026 0.101 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.465 0.022 0.09 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.487 0.026 0.085 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.512 0.022 0.075 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.534 0.026 0.071 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.56 0.022 0.062 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.582 0.018 0.06 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.599 0.022 0.063 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.621 0.018 0.061 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.639 0.022 0.066 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.66 0.018 0.064 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.678 0.022 0.069 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.7 0.018 0.069 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.718 0.022 0.075 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.739 0.018 0.076 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.757 0.022 0.083 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.778 0.025 0.084 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.804 0.021 0.08 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.825 0.025 0.083 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.851 0.021 0.08 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.872 0.025 0.084 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.897 0.029 0.082 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.926 0.025 0.075 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.952 0.029 0.074 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.981 0.025 0.068 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.006 0.029 0.068 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.035 0.025 0.063 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.06 0.029 0.064 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.089 0.025 0.06 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.115 0.029 0.062 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.144 0.025 0.058 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.169 0.029 0.061 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.198 0.025 0.058 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.223 0.029 0.061 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.252 0.025 0.059 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.277 0.029 0.063 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.306 0.025 0.062 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.331 0.029 0.067 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.36 0.033 0.066 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.392 0.029 0.06 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.421 0.025 0.061 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.446 0.029 0.067 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.475 0.025 0.068 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.5 0.021 0.076 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.521 0.025 0.089 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.546 0.029 0.097 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.575 0.025 0.1 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.599 0.021 0.11 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.62 0.025 0.126 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.645 0.029 0.136 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.674 0.032 0.142 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.706 0.036 0.143 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.742 0.04 0.139 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.783 0.036 0.13 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.819 0.04 0.128 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.859 0.044 0.12 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.903 0.048 0.108 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.951 0.044 0.091 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.995 0.048 0.08 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.043 0.044 0.064 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.086 0.048 0.054 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.134 0.044 0.039 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.178 0.048 0.029 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.226 0.044 0.015 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.269 0.04 0.006 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.309 0.036 0.004 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.345 0.032 0.007 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.377 0.036 0.016 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.413 0.032 0.019 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 97 lasted for 126 time steps with total reward of 125.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.025 -0.005 0.016 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.03 -0.001 0.022 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.031 -0.005 0.022 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.036 -0.009 0.028 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.045 -0.005 0.04 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.049 -0.009 0.046 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.058 -0.005 0.058 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.063 -0.009 0.065 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.072 -0.005 0.078 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.076 -0.009 0.085 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.085 -0.005 0.099 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.09 -0.001 0.108 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.091 -0.005 0.111 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.096 -0.001 0.121 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.097 -0.005 0.126 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.102 -0.001 0.137 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.103 0.003 0.143 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.101 0.007 0.144 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.094 0.003 0.141 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.092 0.006 0.144 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.085 0.01 0.142 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.075 0.014 0.136 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.061 0.018 0.124 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.043 0.022 0.108 -0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.021 0.018 0.086 -0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.003 0.022 0.071 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.019 0.018 0.051 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.037 0.014 0.037 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.051 0.018 0.029 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.069 0.014 0.016 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.083 0.01 0.008 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.093 0.006 0.007 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.099 0.002 0.011 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.102 -0.002 0.021 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.1 0.002 0.038 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.102 -0.002 0.048 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.101 0.002 0.065 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.103 -0.002 0.076 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.101 0.002 0.093 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.104 -0.002 0.105 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.102 0.002 0.123 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.104 0.006 0.137 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.11 0.01 0.145 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.12 0.006 0.148 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.126 0.01 0.158 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.136 0.014 0.163 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.149 0.018 0.163 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.167 0.021 0.159 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.188 0.017 0.15 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.206 0.021 0.147 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.227 0.025 0.14 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.252 0.029 0.128 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.281 0.033 0.111 -0.022 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.314 0.037 0.089 -0.027 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.35 0.033 0.062 -0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.383 0.037 0.041 -0.026 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.42 0.033 0.015 -0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.453 0.029 -0.005 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.482 0.025 -0.019 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.506 0.021 -0.027 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.528 0.017 -0.03 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.545 0.013 -0.027 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.558 0.009 -0.018 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.567 0.005 -0.004 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.573 0.009 0.016 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.582 0.005 0.031 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.588 0.009 0.051 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.597 0.005 0.066 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.602 0.009 0.086 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.612 0.013 0.102 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.625 0.017 0.112 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.642 0.013 0.117 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.655 0.017 0.128 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.672 0.021 0.134 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.693 0.017 0.136 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.71 0.021 0.143 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.731 0.025 0.146 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.756 0.021 0.145 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.776 0.025 0.149 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.801 0.028 0.149 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.829 0.032 0.144 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.862 0.036 0.135 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.898 0.04 0.12 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.938 0.036 0.101 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.974 0.04 0.087 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.014 0.036 0.069 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.05 0.04 0.057 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.09 0.036 0.04 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.126 0.032 0.029 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.158 0.028 0.024 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.186 0.032 0.025 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.218 0.028 0.021 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.246 0.024 0.022 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.27 0.028 0.03 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.299 0.024 0.031 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.323 0.02 0.039 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.343 0.024 0.053 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.367 0.02 0.061 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.388 0.024 0.075 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.412 0.028 0.084 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.44 0.024 0.088 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.464 0.028 0.098 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.492 0.024 0.102 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.516 0.028 0.114 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.544 0.032 0.119 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.576 0.036 0.12 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.611 0.04 0.116 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.651 0.036 0.107 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.687 0.039 0.104 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.726 0.043 0.096 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.769 0.039 0.083 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.809 0.043 0.076 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.852 0.039 0.064 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.892 0.035 0.059 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.927 0.039 0.059 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.966 0.035 0.054 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.002 0.039 0.056 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.041 0.035 0.052 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.076 0.039 0.054 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.116 0.035 0.05 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.151 0.039 0.053 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.19 0.035 0.05 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.226 0.031 0.053 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.257 0.035 0.063 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.292 0.031 0.067 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.324 0.035 0.077 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.359 0.039 0.082 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.398 0.035 0.081 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.433 0.039 0.087 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[0, 0]]) selected_action: tensor([0]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 98 lasted for 130 time steps with total reward of 129.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.035 -0.004 -0.033 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.03 -0.008 -0.027 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.022 -0.012 -0.015 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.01 -0.008 0.002 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.002 -0.012 0.013 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.01 -0.008 0.03 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.019 -0.012 0.042 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.031 -0.016 0.059 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.047 -0.012 0.082 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.059 -0.008 0.1 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.067 -0.012 0.113 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.08 -0.008 0.132 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.088 -0.012 0.146 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.1 -0.008 0.167 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.109 -0.005 0.183 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.114 -0.001 0.194 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.114 0.003 0.2 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.111 0.007 0.202 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.104 0.011 0.2 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.094 0.015 0.193 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.079 0.018 0.181 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.061 0.022 0.165 -0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.038 0.018 0.145 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.02 0.022 0.131 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.002 0.026 0.112 -0.024 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.028 0.022 0.089 -0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.05 0.026 0.071 -0.022 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.076 0.022 0.049 -0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.098 0.018 0.033 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.117 0.022 0.023 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.139 0.018 0.007 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.157 0.014 -0.002 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.171 0.01 -0.006 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.181 0.014 -0.004 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.196 0.01 -0.008 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.206 0.006 -0.006 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.212 0.003 0.002 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.215 0.006 0.016 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.221 0.003 0.024 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.224 -0.001 0.038 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.222 0.003 0.057 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.225 0.006 0.072 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.231 0.002 0.08 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.234 0.006 0.095 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.24 0.002 0.105 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.243 0.006 0.121 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.249 0.01 0.132 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.259 0.014 0.138 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.273 0.01 0.139 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.283 0.014 0.146 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.297 0.018 0.149 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.315 0.022 0.147 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.337 0.018 0.14 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.354 0.022 0.139 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.376 0.025 0.134 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.401 0.021 0.124 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.423 0.025 0.12 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.448 0.029 0.112 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.477 0.025 0.098 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.503 0.029 0.091 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.532 0.025 0.079 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.557 0.029 0.073 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.586 0.025 0.062 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.611 0.029 0.057 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.641 0.025 0.046 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.666 0.029 0.042 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.695 0.025 0.032 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.72 0.029 0.029 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.749 0.025 0.019 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.774 0.029 0.016 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.803 0.025 0.007 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.828 0.029 0.004 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.857 0.025 -0.005 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.882 0.021 -0.008 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.904 0.017 -0.005 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.921 0.021 0.004 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.942 0.017 0.007 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.959 0.013 0.015 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.973 0.009 0.03 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.982 0.006 0.05 0.027 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.988 0.009 0.077 0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.997 0.013 0.098 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.011 0.009 0.114 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.02 0.013 0.136 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.033 0.017 0.153 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.051 0.021 0.165 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.072 0.025 0.172 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.096 0.029 0.175 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.125 0.033 0.172 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.158 0.036 0.166 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.194 0.032 0.154 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.227 0.036 0.149 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.263 0.04 0.14 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.303 0.036 0.126 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.339 0.04 0.118 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.379 0.036 0.105 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.416 0.04 0.099 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.456 0.036 0.088 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.492 0.04 0.083 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.532 0.044 0.073 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.576 0.04 0.057 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.616 0.044 0.048 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.659 0.04 0.034 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.699 0.036 0.025 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.735 0.032 0.023 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.767 0.028 0.026 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.796 0.032 0.036 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.828 0.028 0.04 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.856 0.024 0.05 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.88 0.028 0.066 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.908 0.024 0.076 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.932 0.028 0.093 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.96 0.032 0.105 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.992 0.028 0.111 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.02 0.032 0.123 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.052 0.036 0.131 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.088 0.032 0.134 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.12 0.036 0.143 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.156 0.04 0.147 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.195 0.043 0.146 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.239 0.047 0.141 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.286 0.051 0.13 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.337 0.047 0.115 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.384 0.051 0.106 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.435 0.055 0.092 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[0, 0]]) selected_action: tensor([0]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 99 lasted for 126 time steps with total reward of 125.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.001 -0.004 0.024 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.002 -0.008 0.03 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.01 -0.004 0.043 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.014 -0.008 0.05 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.021 -0.004 0.063 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.025 -0.008 0.07 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.033 -0.004 0.084 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.037 -0.008 0.092 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.044 -0.004 0.107 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.048 -0.008 0.116 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.056 -0.004 0.132 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.06 -0.0 0.143 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.06 -0.004 0.149 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.064 -0.0 0.161 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.064 0.004 0.169 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.061 0.008 0.172 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.053 0.011 0.17 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.042 0.015 0.164 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.026 0.019 0.153 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.007 0.023 0.137 -0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.016 0.019 0.116 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.035 0.023 0.102 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.057 0.027 0.083 -0.024 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.084 0.023 0.059 -0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.107 0.027 0.041 -0.023 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.134 0.023 0.017 -0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.157 0.019 -0.0 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.175 0.015 -0.011 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.19 0.011 -0.017 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.202 0.007 -0.017 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.209 0.003 -0.011 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.212 0.007 0.001 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.219 0.003 0.007 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.223 -0.001 0.019 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.222 0.003 0.036 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.225 -0.001 0.048 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.225 0.003 0.066 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.228 -0.001 0.079 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.227 0.003 0.097 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.23 0.007 0.111 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.238 0.003 0.119 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.241 0.007 0.133 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.248 0.011 0.143 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.259 0.015 0.148 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.273 0.011 0.147 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.284 0.015 0.154 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.299 0.019 0.155 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.317 0.022 0.152 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.34 0.026 0.144 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.366 0.022 0.131 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.388 0.026 0.125 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.414 0.03 0.114 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.444 0.026 0.098 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.471 0.03 0.088 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.5 0.026 0.073 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.526 0.03 0.065 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.556 0.026 0.051 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.582 0.03 0.044 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.612 0.026 0.03 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.638 0.022 0.023 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.66 0.026 0.023 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.686 0.022 0.016 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.708 0.026 0.015 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.734 0.022 0.009 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.756 0.018 0.008 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.774 0.014 0.014 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.789 0.018 0.025 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.807 0.014 0.031 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.821 0.01 0.043 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.831 0.014 0.06 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.845 0.01 0.072 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.856 0.014 0.091 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.87 0.01 0.103 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.88 0.014 0.123 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.894 0.018 0.137 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.912 0.022 0.146 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.934 0.026 0.15 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.96 0.03 0.15 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.989 0.026 0.144 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.015 0.029 0.145 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.044 0.033 0.142 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.078 0.037 0.133 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.115 0.033 0.12 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.148 0.037 0.113 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.185 0.033 0.101 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.218 0.037 0.095 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.255 0.041 0.085 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.296 0.037 0.069 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.333 0.033 0.06 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.366 0.037 0.057 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.403 0.033 0.048 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.436 0.029 0.046 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.465 0.033 0.049 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.498 0.029 0.048 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.527 0.033 0.052 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.56 0.029 0.051 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.589 0.025 0.056 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.615 0.029 0.067 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.644 0.025 0.072 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.669 0.029 0.084 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.698 0.033 0.091 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.731 0.029 0.092 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.76 0.033 0.1 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.792 0.029 0.102 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.821 0.033 0.111 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.854 0.029 0.115 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.883 0.033 0.125 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.916 0.037 0.13 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.952 0.033 0.13 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.985 0.036 0.137 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.021 0.04 0.138 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.062 0.044 0.135 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.106 0.048 0.127 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.154 0.044 0.114 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.198 0.048 0.107 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.246 0.044 0.096 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.29 0.04 0.09 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.33 0.044 0.092 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.374 0.04 0.088 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.414 0.044 0.09 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[0, 0]]) selected_action: tensor([0]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 100 lasted for 121 time steps with total reward of 120.0\n",
            "\n",
            "\n",
            " Model saved!\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.027 -0.004 0.002 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.031 -0.008 0.008 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.039 -0.011 0.021 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.05 -0.008 0.039 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.058 -0.012 0.052 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.069 -0.008 0.071 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.077 -0.012 0.084 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.088 -0.008 0.104 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.096 -0.004 0.118 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.1 -0.008 0.127 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.108 -0.004 0.142 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.111 0.0 0.153 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.111 0.004 0.159 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.108 0.008 0.16 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.1 0.004 0.156 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.096 0.008 0.159 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.088 0.011 0.157 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.077 0.015 0.15 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.062 0.011 0.139 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.05 0.015 0.134 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.035 0.019 0.124 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.016 0.015 0.11 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.001 0.019 0.102 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.018 0.015 0.089 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.033 0.019 0.082 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.052 0.015 0.07 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.067 0.019 0.064 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.086 0.015 0.053 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.101 0.019 0.048 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.12 0.015 0.038 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.135 0.011 0.034 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.146 0.015 0.036 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.161 0.011 0.032 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.172 0.015 0.035 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.187 0.011 0.031 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.198 0.007 0.034 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.206 0.011 0.043 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.217 0.015 0.046 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.231 0.011 0.044 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.242 0.007 0.048 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.25 0.011 0.058 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.261 0.007 0.062 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.268 0.011 0.073 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.279 0.007 0.078 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.286 0.011 0.089 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.296 0.007 0.095 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.303 0.011 0.108 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.314 0.015 0.115 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.329 0.019 0.117 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.348 0.015 0.114 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.362 0.019 0.118 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.381 0.022 0.116 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.403 0.018 0.11 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.422 0.022 0.11 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.444 0.018 0.105 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.462 0.022 0.106 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.484 0.026 0.102 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.511 0.022 0.093 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.533 0.026 0.091 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.559 0.03 0.083 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.589 0.026 0.07 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.615 0.022 0.063 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.637 0.026 0.063 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.663 0.022 0.057 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.685 0.026 0.057 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.711 0.022 0.052 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.733 0.018 0.053 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.751 0.022 0.061 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.773 0.018 0.063 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.791 0.022 0.071 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.813 0.026 0.073 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.839 0.022 0.07 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.861 0.026 0.074 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.887 0.022 0.072 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.909 0.026 0.076 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.934 0.022 0.075 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.956 0.026 0.081 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.982 0.022 0.081 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.004 0.026 0.087 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.029 0.022 0.088 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.051 0.026 0.095 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.077 0.022 0.097 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.098 0.026 0.106 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.124 0.029 0.109 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.153 0.026 0.107 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.179 0.029 0.112 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.208 0.025 0.111 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.234 0.029 0.117 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.263 0.033 0.118 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.296 0.037 0.114 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.333 0.033 0.105 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.366 0.037 0.102 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.403 0.041 0.094 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.444 0.037 0.081 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.481 0.041 0.074 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.522 0.037 0.063 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.559 0.041 0.057 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.6 0.037 0.046 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.636 0.041 0.041 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.677 0.037 0.03 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.714 0.041 0.026 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.755 0.037 0.016 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.792 0.041 0.012 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.832 0.037 0.002 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.869 0.033 -0.001 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.902 0.037 0.001 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.939 0.033 -0.003 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.972 0.029 -0.001 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.001 0.025 0.007 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.026 0.029 0.02 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.055 0.025 0.028 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.08 0.021 0.042 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.101 0.025 0.062 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.126 0.021 0.077 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.147 0.025 0.097 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.172 0.029 0.112 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.201 0.025 0.122 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.226 0.029 0.139 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.255 0.033 0.15 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.288 0.037 0.157 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.324 0.04 0.159 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.365 0.044 0.156 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.409 0.04 0.148 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 101 lasted for 124 time steps with total reward of 123.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.008 -0.004 -0.014 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.003 -0.008 -0.008 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.005 -0.012 0.005 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.017 -0.008 0.023 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.026 -0.012 0.035 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.038 -0.016 0.054 0.025 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.054 -0.012 0.078 0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.066 -0.008 0.097 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.075 -0.012 0.111 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.087 -0.008 0.131 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.095 -0.005 0.146 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.1 -0.001 0.156 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.101 -0.005 0.161 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.105 -0.001 0.173 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.106 0.003 0.18 0.002 output tensor([[12, 16]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.103 0.007 0.183 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.096 0.003 0.181 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.093 0.007 0.186 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.087 0.011 0.186 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.076 0.014 0.181 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.062 0.018 0.172 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.043 0.014 0.159 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.029 0.018 0.152 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.011 0.022 0.14 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.011 0.018 0.124 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.03 0.022 0.114 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.052 0.018 0.099 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.07 0.022 0.091 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.092 0.026 0.078 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.117 0.022 0.059 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.139 0.018 0.047 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.157 0.022 0.04 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.179 0.018 0.029 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.197 0.014 0.023 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.211 0.018 0.023 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.229 0.014 0.018 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.243 0.018 0.019 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.261 0.014 0.014 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.275 0.01 0.015 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.285 0.006 0.022 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.291 0.01 0.035 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.301 0.006 0.042 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.308 0.01 0.055 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.318 0.014 0.063 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.332 0.01 0.065 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.342 0.014 0.073 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.356 0.01 0.076 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.366 0.014 0.085 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.38 0.01 0.089 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.389 0.014 0.099 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.403 0.01 0.104 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.413 0.014 0.116 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.427 0.018 0.122 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.445 0.022 0.123 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.466 0.018 0.119 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.484 0.021 0.122 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.505 0.025 0.119 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.53 0.021 0.112 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.552 0.025 0.111 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.577 0.029 0.105 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.606 0.025 0.094 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.631 0.029 0.089 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.66 0.025 0.08 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.686 0.029 0.076 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.715 0.025 0.067 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.74 0.021 0.065 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.761 0.025 0.069 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.786 0.029 0.067 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.815 0.025 0.06 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.84 0.029 0.059 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.869 0.025 0.053 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.894 0.029 0.053 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.922 0.025 0.048 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.947 0.021 0.048 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.968 0.025 0.055 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.993 0.021 0.056 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.014 0.025 0.064 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.039 0.021 0.066 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.06 0.025 0.074 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.085 0.029 0.077 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.114 0.025 0.074 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.139 0.029 0.078 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.167 0.025 0.076 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.192 0.029 0.081 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.221 0.033 0.08 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.253 0.029 0.074 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.282 0.032 0.075 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.314 0.029 0.07 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.343 0.032 0.071 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.375 0.029 0.067 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.404 0.032 0.069 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.436 0.036 0.066 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.472 0.032 0.057 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.505 0.036 0.055 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.541 0.032 0.047 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.573 0.028 0.045 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.602 0.032 0.05 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.634 0.028 0.049 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.662 0.024 0.054 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.687 0.028 0.065 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.715 0.024 0.071 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.74 0.028 0.083 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.768 0.024 0.089 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.792 0.028 0.102 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.821 0.024 0.11 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.845 0.028 0.124 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.873 0.032 0.133 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.905 0.036 0.137 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.941 0.04 0.136 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.981 0.044 0.13 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.025 0.04 0.119 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.064 0.044 0.115 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.108 0.04 0.106 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.147 0.044 0.103 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.191 0.047 0.095 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.238 0.043 0.082 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.282 0.047 0.076 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.329 0.043 0.064 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.373 0.047 0.058 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.42 0.043 0.047 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "output tensor([[0, 0]]) selected_action: tensor([0]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 102 lasted for 121 time steps with total reward of 120.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.009 -0.003 -0.041 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.012 -0.007 -0.035 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.019 -0.011 -0.023 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.03 -0.007 -0.006 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.038 -0.011 0.005 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.049 -0.015 0.022 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.064 -0.019 0.045 0.029 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.083 -0.015 0.073 0.023 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.098 -0.011 0.097 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.109 -0.015 0.114 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.124 -0.011 0.139 0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.135 -0.007 0.158 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.142 -0.003 0.172 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.146 0.0 0.182 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.145 -0.004 0.187 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.149 0.0 0.198 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.148 0.004 0.205 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.144 0.008 0.208 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.136 0.012 0.206 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.124 0.016 0.2 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.109 0.019 0.189 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.089 0.016 0.174 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.074 0.019 0.166 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.054 0.023 0.153 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.031 0.027 0.136 -0.022 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.004 0.023 0.113 -0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.019 0.027 0.098 -0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.046 0.031 0.077 -0.026 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.077 0.027 0.051 -0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.104 0.023 0.031 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.127 0.019 0.018 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.146 0.015 0.01 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.161 0.019 0.008 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.18 0.015 0.001 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.196 0.019 -0.0 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.215 0.015 -0.008 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.23 0.011 -0.009 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.241 0.007 -0.005 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.249 0.011 0.005 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.26 0.007 0.01 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.268 0.004 0.02 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.271 0.007 0.036 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.279 0.004 0.046 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.282 0.007 0.063 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.289 0.003 0.074 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.293 0.007 0.091 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.3 0.003 0.103 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.304 0.007 0.121 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.311 0.011 0.134 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.322 0.007 0.142 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.329 0.011 0.156 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.341 0.015 0.166 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.355 0.011 0.171 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.366 0.015 0.182 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.381 0.019 0.189 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.4 0.023 0.192 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.423 0.026 0.189 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.449 0.03 0.183 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.479 0.026 0.171 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.505 0.03 0.167 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.536 0.034 0.158 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.57 0.038 0.144 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.607 0.042 0.126 -0.023 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.649 0.038 0.102 -0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.687 0.042 0.085 -0.022 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.728 0.038 0.063 -0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.766 0.034 0.048 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.8 0.038 0.038 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.838 0.034 0.023 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.871 0.03 0.014 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.901 0.026 0.012 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.927 0.022 0.015 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.949 0.026 0.024 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.975 0.022 0.027 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.997 0.018 0.036 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.015 0.022 0.051 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.037 0.018 0.061 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.055 0.022 0.077 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.077 0.018 0.087 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.095 0.022 0.104 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.117 0.018 0.115 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.135 0.022 0.133 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.157 0.026 0.146 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.183 0.022 0.154 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.205 0.026 0.168 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.23 0.029 0.178 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.26 0.033 0.183 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.293 0.037 0.183 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.33 0.041 0.179 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.371 0.045 0.17 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.416 0.041 0.157 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.457 0.045 0.15 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.502 0.049 0.138 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.55 0.052 0.122 -0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.603 0.049 0.101 -0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.651 0.052 0.086 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.704 0.049 0.066 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.752 0.052 0.053 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.805 0.048 0.034 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.853 0.045 0.021 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.898 0.048 0.015 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.946 0.045 0.002 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.991 0.041 -0.004 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.032 0.037 -0.005 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.068 0.033 0.001 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.101 0.029 0.012 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.13 0.025 0.029 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.155 0.029 0.052 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.184 0.025 0.069 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.209 0.029 0.092 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.238 0.025 0.11 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.263 0.029 0.135 0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.292 0.033 0.154 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.324 0.037 0.168 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.361 0.04 0.178 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.401 0.044 0.183 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 103 lasted for 117 time steps with total reward of 116.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.039 -0.003 -0.046 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.036 -0.007 -0.041 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.029 -0.011 -0.031 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.017 -0.015 -0.015 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.002 -0.011 0.007 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.009 -0.015 0.023 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.024 -0.019 0.044 0.028 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.042 -0.023 0.072 0.034 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.065 -0.019 0.106 0.028 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.084 -0.023 0.134 0.035 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.107 -0.019 0.169 0.03 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.126 -0.015 0.198 0.025 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.141 -0.011 0.224 0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 104 lasted for 14 time steps with total reward of 13.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.025 -0.005 0.008 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.02 -0.009 0.013 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.011 -0.005 0.025 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.006 -0.009 0.03 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.002 -0.013 0.042 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.015 -0.009 0.059 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.024 -0.013 0.071 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.037 -0.009 0.09 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.045 -0.013 0.102 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.058 -0.009 0.122 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.067 -0.005 0.136 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.072 -0.001 0.145 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.073 -0.005 0.149 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.078 -0.001 0.16 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.08 0.003 0.166 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.077 -0.001 0.167 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.078 0.003 0.175 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.076 0.006 0.178 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.069 0.01 0.177 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.059 0.006 0.17 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.053 0.01 0.171 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.043 0.014 0.167 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.029 0.018 0.159 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.011 0.014 0.146 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.003 0.018 0.139 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.021 0.022 0.128 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.042 0.018 0.111 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.06 0.022 0.102 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.081 0.018 0.087 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.099 0.021 0.079 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.12 0.025 0.065 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.146 0.021 0.046 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.167 0.025 0.033 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.192 0.021 0.015 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.214 0.017 0.003 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.231 0.014 -0.004 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.245 0.01 -0.004 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.255 0.006 0.001 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.26 0.01 0.013 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.27 0.006 0.018 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.276 0.002 0.029 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.278 0.006 0.047 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.284 0.002 0.058 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.285 0.006 0.076 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.291 0.002 0.088 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.293 0.006 0.107 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.299 0.002 0.12 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.3 0.006 0.14 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.306 0.009 0.155 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.316 0.013 0.165 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.329 0.017 0.17 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.346 0.013 0.17 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.359 0.017 0.177 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.376 0.021 0.18 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.397 0.025 0.178 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.422 0.021 0.171 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.443 0.025 0.171 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.468 0.029 0.166 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.496 0.032 0.157 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.529 0.028 0.143 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.557 0.032 0.136 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.589 0.036 0.124 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.626 0.032 0.107 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.658 0.036 0.096 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.694 0.032 0.08 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.726 0.036 0.071 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.762 0.032 0.057 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.794 0.036 0.048 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.83 0.032 0.035 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.862 0.028 0.027 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.891 0.024 0.025 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.915 0.02 0.03 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.935 0.024 0.04 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.959 0.028 0.045 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.988 0.024 0.045 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.012 0.028 0.05 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.04 0.024 0.05 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.064 0.028 0.056 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.092 0.024 0.056 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.116 0.028 0.063 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.145 0.024 0.064 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.169 0.028 0.071 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.197 0.024 0.073 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.221 0.028 0.081 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.249 0.024 0.084 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.273 0.028 0.094 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.301 0.024 0.097 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.325 0.028 0.108 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.353 0.032 0.113 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.385 0.036 0.113 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.42 0.032 0.108 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.452 0.036 0.109 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.487 0.039 0.105 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.527 0.036 0.096 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.562 0.039 0.094 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.602 0.043 0.086 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.645 0.039 0.074 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.684 0.043 0.067 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.727 0.039 0.055 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.767 0.043 0.05 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.81 0.039 0.039 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.849 0.043 0.034 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.892 0.039 0.023 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.932 0.035 0.019 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.967 0.031 0.02 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.998 0.035 0.028 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.034 0.031 0.029 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.065 0.035 0.037 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.1 0.039 0.039 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.14 0.035 0.036 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.175 0.039 0.038 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.214 0.035 0.035 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.249 0.031 0.038 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.281 0.035 0.048 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.316 0.031 0.051 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.347 0.035 0.061 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.382 0.031 0.065 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.414 0.035 0.075 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[0, 0]]) selected_action: tensor([0]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 105 lasted for 119 time steps with total reward of 118.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.016 -0.004 -0.04 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.02 -0.008 -0.035 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.028 -0.012 -0.025 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.04 -0.016 -0.008 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.056 -0.012 0.014 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.069 -0.016 0.03 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.085 -0.012 0.052 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.097 -0.016 0.068 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.113 -0.012 0.091 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.125 -0.016 0.108 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.141 -0.012 0.132 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.154 -0.008 0.15 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.162 -0.005 0.164 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.167 -0.008 0.172 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.175 -0.005 0.188 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.18 -0.001 0.199 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.18 0.003 0.205 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.177 0.007 0.206 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.171 0.011 0.204 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.16 0.015 0.197 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.145 0.018 0.185 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.127 0.022 0.169 -0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.105 0.018 0.148 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.086 0.022 0.134 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.064 0.026 0.116 -0.024 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.038 0.022 0.092 -0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.016 0.026 0.075 -0.022 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.01 0.022 0.052 -0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.032 0.018 0.036 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.05 0.014 0.026 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.064 0.018 0.022 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.082 0.014 0.013 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.096 0.01 0.009 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.107 0.014 0.012 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.121 0.01 0.008 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.131 0.006 0.011 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.137 0.01 0.019 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.148 0.006 0.022 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.154 0.002 0.031 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.157 0.006 0.045 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.163 0.002 0.054 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.165 0.006 0.069 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.172 0.002 0.079 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.174 0.006 0.095 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.18 0.002 0.105 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.183 0.006 0.122 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.189 0.01 0.134 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.199 0.006 0.141 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.205 0.01 0.154 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.215 0.014 0.163 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.229 0.018 0.166 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.247 0.022 0.165 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.268 0.025 0.16 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.294 0.021 0.149 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.315 0.025 0.145 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.34 0.029 0.137 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.37 0.033 0.123 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.403 0.037 0.105 -0.023 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.44 0.033 0.081 -0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.472 0.029 0.065 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.502 0.033 0.054 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.534 0.029 0.038 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.563 0.033 0.028 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.596 0.029 0.013 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.625 0.025 0.003 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.65 0.021 -0.0 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.672 0.017 0.002 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.689 0.021 0.01 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.71 0.017 0.013 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.727 0.013 0.021 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.741 0.017 0.035 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.758 0.013 0.044 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.771 0.009 0.058 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.781 0.013 0.079 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.794 0.017 0.094 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.811 0.013 0.104 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.825 0.017 0.12 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.842 0.021 0.132 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.863 0.017 0.138 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.88 0.021 0.15 0.008 output tensor([[12, 16]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.901 0.017 0.158 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.918 0.021 0.173 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.939 0.025 0.182 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.964 0.021 0.187 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.984 0.025 0.199 0.007 output tensor([[12, 16]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.009 0.028 0.207 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.037 0.024 0.21 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 106 lasted for 88 time steps with total reward of 87.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.046 -0.004 -0.039 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.042 -0.008 -0.033 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.034 -0.012 -0.022 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.022 -0.016 -0.005 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.006 -0.012 0.017 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.006 -0.016 0.034 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.022 -0.012 0.056 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.034 -0.016 0.073 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.051 -0.012 0.096 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.063 -0.016 0.114 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.079 -0.012 0.138 0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.091 -0.008 0.157 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.099 -0.012 0.172 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.112 -0.008 0.192 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.12 -0.005 0.209 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.125 -0.001 0.22 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 107 lasted for 17 time steps with total reward of 16.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.039 -0.003 0.014 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.036 0.001 0.02 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.037 -0.003 0.02 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.035 -0.007 0.026 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.028 -0.011 0.037 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.017 -0.007 0.055 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.01 -0.011 0.067 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.001 -0.007 0.086 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.008 -0.011 0.099 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.018 -0.007 0.118 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.025 -0.003 0.132 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.028 0.001 0.141 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.028 -0.003 0.145 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.031 0.001 0.156 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.03 0.005 0.162 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.025 0.008 0.163 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.017 0.012 0.159 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.005 0.016 0.151 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.011 0.012 0.137 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.024 0.016 0.131 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.04 0.02 0.12 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.059 0.024 0.103 -0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.083 0.02 0.082 -0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.103 0.024 0.067 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.127 0.02 0.046 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.147 0.016 0.032 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.162 0.012 0.025 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.174 0.016 0.023 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.19 0.012 0.015 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.202 0.008 0.014 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.21 0.004 0.018 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.214 0.008 0.028 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.223 0.004 0.033 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.227 0.008 0.044 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.235 0.004 0.049 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.239 0.008 0.06 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.247 0.004 0.065 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.251 0.008 0.077 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.259 0.004 0.083 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.263 0.0 0.096 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.263 0.004 0.115 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.267 0.008 0.129 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.275 0.012 0.138 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.287 0.016 0.141 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.302 0.019 0.14 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.322 0.015 0.134 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.337 0.019 0.135 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.356 0.023 0.13 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.38 0.019 0.121 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.399 0.023 0.118 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.422 0.019 0.111 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.441 0.023 0.11 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.464 0.027 0.103 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.491 0.023 0.092 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.514 0.027 0.087 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.541 0.031 0.077 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.572 0.027 0.061 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.599 0.031 0.052 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.63 0.027 0.037 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.656 0.031 0.029 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.687 0.027 0.015 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.714 0.023 0.007 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.737 0.019 0.005 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.756 0.015 0.009 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.771 0.019 0.018 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.79 0.015 0.022 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.805 0.019 0.032 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.824 0.015 0.036 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.839 0.011 0.046 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.85 0.015 0.063 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.865 0.011 0.073 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.876 0.015 0.09 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.891 0.019 0.102 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.91 0.015 0.108 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.925 0.019 0.121 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.944 0.015 0.129 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.959 0.019 0.143 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.978 0.023 0.152 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.0 0.026 0.156 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.027 0.03 0.156 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.057 0.026 0.151 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.083 0.03 0.152 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.113 0.034 0.149 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.148 0.03 0.14 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.178 0.034 0.139 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.212 0.038 0.133 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.25 0.034 0.121 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.283 0.038 0.117 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.321 0.034 0.107 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.355 0.038 0.104 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.393 0.034 0.095 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.427 0.038 0.094 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.464 0.042 0.086 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.506 0.038 0.074 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.543 0.041 0.068 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.585 0.038 0.057 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.622 0.034 0.052 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.656 0.038 0.053 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.694 0.034 0.049 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.727 0.03 0.05 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.757 0.034 0.058 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.791 0.037 0.061 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.828 0.034 0.058 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.862 0.03 0.061 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.891 0.034 0.07 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.925 0.037 0.074 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.962 0.033 0.073 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.996 0.037 0.078 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.033 0.033 0.077 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.067 0.037 0.083 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.104 0.033 0.084 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.137 0.037 0.09 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.175 0.033 0.092 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.208 0.037 0.1 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.245 0.041 0.102 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.286 0.037 0.1 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.323 0.041 0.104 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.364 0.045 0.103 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.409 0.041 0.096 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 108 lasted for 120 time steps with total reward of 119.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.022 -0.003 -0.01 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.019 -0.007 -0.004 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.011 -0.011 0.009 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.0 -0.007 0.027 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.007 -0.011 0.04 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.018 -0.015 0.058 0.025 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.033 -0.011 0.083 0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.044 -0.015 0.102 0.026 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.059 -0.011 0.128 0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.07 -0.007 0.148 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.078 -0.003 0.163 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.081 0.0 0.174 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.081 0.004 0.18 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.077 0.0 0.181 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.076 0.004 0.189 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.072 0.008 0.192 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.064 0.012 0.191 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.053 0.016 0.185 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.037 0.019 0.175 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.017 0.023 0.16 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.006 0.019 0.141 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.025 0.023 0.128 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.049 0.027 0.11 -0.023 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.076 0.031 0.088 -0.028 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.107 0.027 0.06 -0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.134 0.031 0.039 -0.027 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.165 0.027 0.012 -0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.192 0.023 -0.009 -0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.215 0.019 -0.024 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.234 0.015 -0.033 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.249 0.011 -0.036 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.261 0.008 -0.034 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.268 0.004 -0.026 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.272 -0.0 -0.012 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.272 0.004 0.007 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.275 -0.0 0.02 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.275 -0.004 0.039 0.025 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.271 -0.0 0.065 0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.271 0.004 0.084 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.274 -0.0 0.098 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.274 -0.004 0.119 0.027 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.27 -0.0 0.146 0.022 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.27 0.004 0.168 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.273 0.007 0.185 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.28 0.003 0.197 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.284 0.007 0.216 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 109 lasted for 47 time steps with total reward of 46.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.045 -0.003 0.016 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.042 -0.007 0.022 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.034 -0.003 0.034 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.031 -0.007 0.041 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.024 -0.011 0.054 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.012 -0.007 0.072 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.005 -0.003 0.085 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.002 -0.007 0.093 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.006 -0.004 0.107 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.009 0.0 0.116 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.009 -0.004 0.12 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.013 0.0 0.13 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.012 0.004 0.135 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.008 0.0 0.136 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.008 0.004 0.143 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.004 0.008 0.145 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.004 0.004 0.142 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.008 0.008 0.145 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.016 0.012 0.144 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.028 0.008 0.138 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.035 0.012 0.139 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.047 0.015 0.135 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.063 0.019 0.126 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.082 0.015 0.111 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.097 0.019 0.104 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.117 0.023 0.091 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.14 0.019 0.074 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.159 0.023 0.062 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.182 0.019 0.045 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.201 0.015 0.035 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.217 0.019 0.031 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.236 0.015 0.021 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.251 0.011 0.017 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.262 0.007 0.019 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.27 0.011 0.026 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.281 0.007 0.029 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.289 0.011 0.037 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.3 0.007 0.04 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.307 0.011 0.048 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.319 0.007 0.051 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.326 0.011 0.06 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.337 0.007 0.064 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.345 0.011 0.074 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.356 0.007 0.079 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.363 0.011 0.089 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.374 0.015 0.095 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.389 0.011 0.095 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.401 0.015 0.101 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.416 0.011 0.103 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.427 0.015 0.111 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.442 0.011 0.113 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.453 0.015 0.122 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.468 0.019 0.127 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.486 0.023 0.126 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.509 0.019 0.12 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.528 0.023 0.12 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.55 0.026 0.116 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.577 0.022 0.106 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.599 0.026 0.103 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.625 0.03 0.095 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.656 0.026 0.082 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.682 0.03 0.075 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.712 0.026 0.063 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.738 0.03 0.057 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.768 0.026 0.046 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.795 0.03 0.041 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.825 0.026 0.03 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.851 0.03 0.025 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.881 0.026 0.015 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.907 0.03 0.011 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.937 0.026 0.001 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.964 0.022 -0.003 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.986 0.026 -0.001 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.012 0.022 -0.005 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.034 0.018 -0.003 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.053 0.014 0.004 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.067 0.011 0.018 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.078 0.014 0.037 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.092 0.011 0.051 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.103 0.014 0.07 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.117 0.011 0.085 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.128 0.014 0.105 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.142 0.018 0.12 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.16 0.014 0.13 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.175 0.018 0.147 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.193 0.022 0.158 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.215 0.026 0.165 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.241 0.022 0.167 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.263 0.026 0.175 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.289 0.03 0.179 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.318 0.033 0.179 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.352 0.037 0.173 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.389 0.033 0.164 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.422 0.037 0.161 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.46 0.041 0.153 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.501 0.045 0.14 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.546 0.041 0.123 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.587 0.045 0.112 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.632 0.049 0.096 -0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.68 0.045 0.075 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.725 0.041 0.061 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.766 0.045 0.053 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.811 0.041 0.039 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.852 0.045 0.032 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.897 0.041 0.019 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.937 0.037 0.012 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.974 0.041 0.011 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.015 0.037 0.004 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.052 0.033 0.003 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.085 0.029 0.008 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.114 0.025 0.019 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.139 0.029 0.036 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.169 0.025 0.047 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.194 0.029 0.064 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.223 0.025 0.076 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.248 0.029 0.094 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.277 0.033 0.106 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.31 0.029 0.113 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.339 0.033 0.127 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.372 0.037 0.136 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.409 0.041 0.139 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[0, 0]]) selected_action: tensor([0]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 110 lasted for 122 time steps with total reward of 121.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.013 -0.005 0.002 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.009 -0.009 0.009 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.0 -0.012 0.021 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.012 -0.009 0.039 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.021 -0.013 0.051 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.034 -0.009 0.069 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.042 -0.005 0.082 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.047 -0.009 0.09 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.056 -0.005 0.103 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.06 -0.001 0.112 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.061 0.003 0.115 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.058 -0.001 0.114 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.059 0.003 0.118 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.056 -0.001 0.118 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.057 0.003 0.124 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.055 -0.001 0.126 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.056 0.003 0.133 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.053 0.007 0.136 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.046 0.003 0.134 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.044 0.007 0.138 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.037 0.01 0.138 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.027 0.014 0.132 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.013 0.018 0.122 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.005 0.014 0.107 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.02 0.018 0.098 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.038 0.014 0.084 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.052 0.018 0.077 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.07 0.014 0.064 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.084 0.018 0.058 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.102 0.014 0.046 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.116 0.01 0.04 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.126 0.014 0.041 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.14 0.01 0.035 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.15 0.006 0.036 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.156 0.01 0.044 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.166 0.006 0.045 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.173 0.01 0.053 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.183 0.006 0.055 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.189 0.01 0.063 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.199 0.006 0.065 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.205 0.01 0.074 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.215 0.006 0.078 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.221 0.01 0.088 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.231 0.006 0.092 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.237 0.01 0.103 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.247 0.006 0.108 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.253 0.01 0.12 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.263 0.014 0.127 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.276 0.018 0.129 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.294 0.014 0.126 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.307 0.017 0.13 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.325 0.021 0.128 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.346 0.017 0.121 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.364 0.021 0.122 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.385 0.017 0.117 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.402 0.021 0.118 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.423 0.017 0.115 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.441 0.021 0.118 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.462 0.025 0.116 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.487 0.021 0.109 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.508 0.025 0.108 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.533 0.029 0.103 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.562 0.033 0.092 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.594 0.029 0.076 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.623 0.033 0.066 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.656 0.029 0.051 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.685 0.033 0.043 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.717 0.029 0.028 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.746 0.025 0.02 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.771 0.029 0.018 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.799 0.025 0.011 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.824 0.021 0.009 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.845 0.017 0.013 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.862 0.021 0.023 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.883 0.017 0.027 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.9 0.013 0.037 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.913 0.017 0.054 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.93 0.013 0.064 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.943 0.017 0.081 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.96 0.013 0.093 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.973 0.017 0.11 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.989 0.021 0.123 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.01 0.017 0.13 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.027 0.021 0.144 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.048 0.025 0.153 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.072 0.021 0.157 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.093 0.024 0.168 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.117 0.028 0.174 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.145 0.032 0.175 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.177 0.036 0.172 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.213 0.04 0.164 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.253 0.044 0.151 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.297 0.048 0.134 -0.022 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.344 0.044 0.112 -0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.388 0.047 0.096 -0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.435 0.044 0.075 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.479 0.04 0.061 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.518 0.043 0.053 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.562 0.04 0.04 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.602 0.036 0.032 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.637 0.032 0.031 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.669 0.036 0.036 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.705 0.032 0.035 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.736 0.028 0.041 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.764 0.032 0.052 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.796 0.028 0.058 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.824 0.032 0.07 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.855 0.028 0.077 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.883 0.032 0.089 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.915 0.036 0.097 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.95 0.039 0.099 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.99 0.035 0.096 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.025 0.039 0.099 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.064 0.035 0.097 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.1 0.039 0.102 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.139 0.043 0.101 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.182 0.047 0.096 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.229 0.043 0.085 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.272 0.047 0.08 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.319 0.043 0.07 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.362 0.039 0.067 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.401 0.043 0.07 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 111 lasted for 123 time steps with total reward of 122.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.045 -0.003 -0.029 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.042 -0.007 -0.024 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.035 -0.011 -0.013 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.024 -0.015 0.003 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.01 -0.011 0.026 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.001 -0.015 0.042 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.016 -0.011 0.065 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.027 -0.015 0.082 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.041 -0.011 0.105 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.052 -0.015 0.123 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.067 -0.011 0.147 0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.077 -0.007 0.166 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.084 -0.003 0.181 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.088 0.001 0.19 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.087 0.005 0.195 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.082 0.008 0.196 -0.004 output tensor([[12, 16]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.074 0.012 0.192 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.062 0.008 0.183 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.053 0.012 0.182 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.041 0.016 0.176 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.025 0.02 0.165 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.005 0.024 0.15 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.018 0.02 0.129 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.038 0.024 0.116 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.061 0.027 0.098 -0.023 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.089 0.024 0.074 -0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.112 0.027 0.057 -0.022 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.14 0.023 0.035 -0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.163 0.02 0.018 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.183 0.016 0.008 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.199 0.02 0.004 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.218 0.016 -0.006 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.234 0.012 -0.01 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.246 0.008 -0.008 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.254 0.012 -0.001 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.265 0.008 0.001 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.273 0.004 0.008 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.277 0.008 0.021 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.285 0.004 0.029 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.289 0.0 0.042 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.289 0.004 0.062 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.293 0.0 0.076 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.293 0.004 0.096 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.297 0.008 0.111 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.305 0.004 0.12 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.309 0.008 0.136 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.316 0.004 0.147 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.32 0.008 0.165 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.328 0.011 0.178 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.339 0.015 0.186 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.355 0.019 0.189 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.374 0.023 0.188 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.397 0.027 0.183 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.424 0.031 0.172 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.454 0.027 0.158 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.481 0.031 0.15 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.512 0.034 0.137 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.546 0.031 0.119 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.577 0.034 0.108 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.611 0.03 0.092 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.642 0.034 0.083 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.676 0.03 0.068 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.706 0.034 0.059 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.741 0.03 0.045 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.771 0.034 0.038 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.805 0.03 0.025 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.836 0.034 0.017 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.87 0.03 0.005 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.9 0.026 -0.002 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.927 0.023 -0.003 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.949 0.026 0.002 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.976 0.023 0.001 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.998 0.019 0.006 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.017 0.015 0.016 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.032 0.019 0.033 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.05 0.015 0.044 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.065 0.019 0.061 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.084 0.015 0.072 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.098 0.019 0.09 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.117 0.015 0.102 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.132 0.019 0.12 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.15 0.022 0.134 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.172 0.018 0.142 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.191 0.022 0.157 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.213 0.026 0.167 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.239 0.022 0.173 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.262 0.026 0.185 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.288 0.03 0.192 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.318 0.026 0.195 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.344 0.03 0.205 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.373 0.034 0.21 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 112 lasted for 92 time steps with total reward of 91.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.034 -0.004 0.006 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.03 -0.008 0.011 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.022 -0.012 0.023 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.01 -0.008 0.04 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.002 -0.012 0.051 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.01 -0.008 0.069 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.018 -0.012 0.081 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.03 -0.008 0.099 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.039 -0.012 0.112 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.051 -0.008 0.132 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.059 -0.004 0.146 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.063 -0.001 0.156 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.064 0.003 0.16 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.06 -0.001 0.16 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.061 0.003 0.166 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.058 0.007 0.168 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.051 0.011 0.165 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.04 0.015 0.157 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.025 0.019 0.145 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.006 0.022 0.128 -0.022 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.016 0.026 0.106 -0.027 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.042 0.022 0.079 -0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.065 0.019 0.058 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.083 0.022 0.044 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.106 0.018 0.024 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.124 0.015 0.01 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.139 0.018 0.003 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.157 0.015 -0.011 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.172 0.011 -0.018 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.183 0.007 -0.02 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.189 0.003 -0.016 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.192 -0.001 -0.007 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.191 -0.005 0.009 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.186 -0.001 0.03 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.185 -0.005 0.046 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.18 -0.001 0.067 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.179 -0.005 0.083 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.174 -0.001 0.105 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.173 -0.005 0.122 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.168 -0.001 0.146 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.167 0.003 0.164 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.17 0.007 0.177 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.176 0.01 0.186 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.187 0.014 0.19 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.201 0.018 0.19 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.219 0.022 0.184 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.241 0.026 0.175 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.267 0.03 0.161 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.296 0.033 0.142 -0.024 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.33 0.03 0.118 -0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.359 0.033 0.101 -0.022 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.393 0.037 0.079 -0.027 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.43 0.033 0.052 -0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.463 0.029 0.031 -0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.493 0.033 0.017 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.526 0.029 -0.004 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.556 0.026 -0.018 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.581 0.022 -0.027 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.603 0.018 -0.029 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.62 0.014 -0.027 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.634 0.01 -0.018 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.644 0.014 -0.004 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.658 0.01 0.004 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.668 0.006 0.018 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.674 0.01 0.038 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.684 0.006 0.053 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.69 0.01 0.073 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.7 0.006 0.088 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.706 0.01 0.109 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.716 0.006 0.125 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.722 0.01 0.147 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.732 0.014 0.164 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.745 0.018 0.177 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.763 0.021 0.184 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.784 0.025 0.187 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.809 0.029 0.186 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.838 0.025 0.18 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.863 0.029 0.181 -0.004 output tensor([[12, 16]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.892 0.025 0.177 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.917 0.029 0.18 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.946 0.033 0.178 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.979 0.037 0.172 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.016 0.033 0.161 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.048 0.036 0.157 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.085 0.04 0.148 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.125 0.036 0.135 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.161 0.04 0.128 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.201 0.044 0.116 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.245 0.048 0.099 -0.022 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.293 0.044 0.078 -0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.337 0.048 0.062 -0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.385 0.044 0.041 -0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.429 0.048 0.027 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.477 0.044 0.007 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.521 0.04 -0.007 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.561 0.036 -0.016 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.597 0.032 -0.018 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.63 0.028 -0.015 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.658 0.024 -0.005 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.682 0.028 0.009 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.711 0.024 0.018 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.735 0.028 0.033 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.764 0.024 0.042 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.788 0.028 0.058 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.816 0.024 0.067 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.841 0.028 0.083 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.869 0.032 0.094 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.901 0.028 0.099 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.93 0.032 0.11 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.962 0.028 0.116 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.99 0.032 0.129 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.022 0.036 0.137 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.058 0.04 0.14 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.098 0.044 0.138 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.141 0.04 0.131 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.181 0.044 0.13 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.225 0.047 0.125 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.272 0.051 0.114 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.323 0.047 0.099 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.371 0.051 0.09 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.422 0.047 0.076 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 113 lasted for 122 time steps with total reward of 121.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.047 -0.005 0.022 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.051 -0.009 0.028 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.06 -0.012 0.039 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.072 -0.009 0.057 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.081 -0.013 0.069 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.094 -0.009 0.087 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.102 -0.005 0.099 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.107 -0.009 0.107 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.116 -0.005 0.121 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.12 -0.009 0.129 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.129 -0.005 0.144 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.134 -0.001 0.155 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.135 -0.005 0.16 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.14 -0.001 0.172 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.141 0.003 0.18 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.138 0.007 0.182 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.132 0.003 0.18 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.129 0.006 0.185 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.123 0.01 0.186 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.112 0.014 0.181 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.098 0.018 0.173 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.08 0.022 0.159 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.059 0.026 0.141 -0.023 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.033 0.022 0.118 -0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.011 0.026 0.102 -0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.015 0.03 0.081 -0.026 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.044 0.026 0.054 -0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.07 0.029 0.034 -0.026 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.099 0.026 0.008 -0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.125 0.022 -0.011 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.146 0.018 -0.025 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.164 0.014 -0.033 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.178 0.01 -0.035 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.188 0.006 -0.031 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.194 0.002 -0.022 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.196 0.006 -0.008 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.202 0.002 0.001 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.204 -0.002 0.016 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.203 -0.006 0.036 0.026 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.197 -0.002 0.063 0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.195 -0.006 0.083 0.027 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.19 -0.002 0.11 0.022 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.188 0.002 0.132 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.19 -0.002 0.149 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.188 0.002 0.172 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.19 0.006 0.19 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.196 0.01 0.204 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.206 0.014 0.213 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 114 lasted for 49 time steps with total reward of 48.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.001 -0.004 -0.02 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.004 -0.008 -0.015 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.012 -0.012 -0.003 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.024 -0.016 0.014 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.04 -0.012 0.037 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.052 -0.008 0.054 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.06 -0.012 0.066 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.072 -0.016 0.083 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.088 -0.012 0.108 0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.1 -0.008 0.126 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.108 -0.004 0.14 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.113 -0.008 0.148 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.121 -0.004 0.164 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.126 -0.001 0.174 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.126 0.003 0.18 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.123 0.007 0.181 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.116 0.011 0.177 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.105 0.015 0.169 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.09 0.011 0.156 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.08 0.015 0.15 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.065 0.019 0.139 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.046 0.015 0.123 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.032 0.018 0.114 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.013 0.015 0.1 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.001 0.018 0.093 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.02 0.022 0.08 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.042 0.018 0.062 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.06 0.014 0.05 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.075 0.018 0.045 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.093 0.014 0.034 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.107 0.018 0.029 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.126 0.014 0.019 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.14 0.018 0.015 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.158 0.014 0.004 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.173 0.01 0.0 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.183 0.007 0.002 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.19 0.01 0.009 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.2 0.007 0.011 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.207 0.003 0.019 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.209 0.007 0.032 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.216 0.003 0.04 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.218 0.007 0.054 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.225 0.003 0.062 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.228 0.006 0.077 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.234 0.003 0.086 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.237 0.006 0.101 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.243 0.01 0.111 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.253 0.006 0.116 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.26 0.01 0.127 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.27 0.006 0.134 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.276 0.01 0.146 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.287 0.014 0.154 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.301 0.018 0.157 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.318 0.022 0.156 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.34 0.026 0.149 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.366 0.029 0.138 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.395 0.026 0.122 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.421 0.029 0.112 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.45 0.033 0.098 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.483 0.029 0.078 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.513 0.033 0.065 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.546 0.029 0.046 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.575 0.025 0.034 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.601 0.029 0.028 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.63 0.025 0.016 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.655 0.021 0.01 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.677 0.025 0.01 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.702 0.021 0.005 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.723 0.018 0.005 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.741 0.021 0.011 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.762 0.018 0.011 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.78 0.014 0.018 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.793 0.01 0.03 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.803 0.014 0.048 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.817 0.01 0.061 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.826 0.014 0.079 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.84 0.01 0.092 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.85 0.014 0.112 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.863 0.017 0.126 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.881 0.021 0.135 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.902 0.025 0.139 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.927 0.021 0.139 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.948 0.025 0.145 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.973 0.029 0.146 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.002 0.033 0.142 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.035 0.037 0.133 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.072 0.033 0.119 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.104 0.037 0.112 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.141 0.04 0.1 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.181 0.036 0.083 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.218 0.04 0.072 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.258 0.036 0.056 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.294 0.033 0.046 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.327 0.029 0.042 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.356 0.032 0.045 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.388 0.029 0.042 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.417 0.032 0.045 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.449 0.029 0.043 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.478 0.032 0.046 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.51 0.029 0.044 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.539 0.032 0.048 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.571 0.029 0.047 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.6 0.025 0.052 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.624 0.028 0.063 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.653 0.025 0.068 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.677 0.028 0.08 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.706 0.032 0.086 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.738 0.028 0.087 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.766 0.024 0.094 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.791 0.028 0.108 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.819 0.032 0.116 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.851 0.028 0.119 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.88 0.032 0.129 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.912 0.028 0.134 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.94 0.032 0.145 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.972 0.036 0.152 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.008 0.04 0.153 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.048 0.036 0.15 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.084 0.04 0.153 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.123 0.044 0.152 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.167 0.04 0.146 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.207 0.043 0.146 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.25 0.047 0.142 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.297 0.051 0.133 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.348 0.055 0.119 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.404 0.051 0.099 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 115 lasted for 127 time steps with total reward of 126.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.023 -0.004 -0.016 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.026 -0.008 -0.011 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.034 -0.011 0.0 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.045 -0.008 0.017 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.053 -0.012 0.027 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.064 -0.015 0.044 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.08 -0.012 0.067 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.091 -0.008 0.084 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.099 -0.012 0.096 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.111 -0.008 0.114 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.118 -0.012 0.127 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.13 -0.008 0.146 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.138 -0.004 0.161 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.142 -0.0 0.17 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.142 0.004 0.175 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.138 0.008 0.175 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.13 0.011 0.17 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.119 0.015 0.161 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.103 0.019 0.147 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.084 0.015 0.129 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.069 0.019 0.117 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.05 0.015 0.1 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.035 0.019 0.089 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.016 0.015 0.074 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.0 0.019 0.064 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.019 0.015 0.05 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.034 0.019 0.042 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.053 0.015 0.028 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.068 0.019 0.02 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.087 0.015 0.006 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.102 0.011 -0.001 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.113 0.015 -0.003 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.128 0.011 -0.01 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.139 0.007 -0.012 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.146 0.003 -0.008 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.15 -0.001 0.002 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.149 0.003 0.018 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.152 -0.001 0.028 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.152 -0.004 0.044 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.147 -0.001 0.066 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.147 0.003 0.082 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.15 -0.001 0.093 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.15 0.003 0.111 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.153 0.007 0.123 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.16 0.011 0.13 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.171 0.007 0.131 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.178 0.011 0.14 0.004 output tensor([[12, 16]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.189 0.015 0.143 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.204 0.011 0.142 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.215 0.015 0.147 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.229 0.019 0.148 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.248 0.022 0.143 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.27 0.026 0.134 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.296 0.022 0.12 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.319 0.026 0.112 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.345 0.022 0.1 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.367 0.026 0.094 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.393 0.022 0.082 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.416 0.026 0.078 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.442 0.022 0.067 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.464 0.026 0.064 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.49 0.022 0.054 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.512 0.026 0.051 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.538 0.022 0.043 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.56 0.018 0.04 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.578 0.022 0.044 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.6 0.018 0.042 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.618 0.022 0.047 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.641 0.018 0.045 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.659 0.014 0.05 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.673 0.018 0.061 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.691 0.014 0.067 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.705 0.018 0.078 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.723 0.022 0.085 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.745 0.018 0.086 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.763 0.022 0.093 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.785 0.018 0.095 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.803 0.022 0.103 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.825 0.026 0.107 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.851 0.022 0.105 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.872 0.026 0.109 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.898 0.03 0.108 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.928 0.026 0.103 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.953 0.029 0.103 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.983 0.033 0.099 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.016 0.029 0.089 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.045 0.033 0.086 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.079 0.029 0.078 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.108 0.033 0.076 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.141 0.029 0.068 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.171 0.033 0.067 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.204 0.037 0.06 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.241 0.033 0.049 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.274 0.029 0.043 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.303 0.033 0.043 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.336 0.029 0.038 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.366 0.033 0.039 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.399 0.029 0.034 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.428 0.025 0.036 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.453 0.029 0.043 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.482 0.025 0.045 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.508 0.021 0.053 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.529 0.025 0.068 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.554 0.029 0.076 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.583 0.025 0.079 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.608 0.029 0.089 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.637 0.033 0.093 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.67 0.029 0.092 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.699 0.025 0.098 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.725 0.029 0.109 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.754 0.033 0.116 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.786 0.029 0.117 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.815 0.033 0.125 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.848 0.037 0.128 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.885 0.033 0.126 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.917 0.037 0.131 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.954 0.04 0.13 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.994 0.044 0.125 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.039 0.04 0.114 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.079 0.044 0.11 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.123 0.04 0.101 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.163 0.044 0.099 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.208 0.04 0.091 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.248 0.044 0.09 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.292 0.04 0.084 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.332 0.044 0.084 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.376 0.04 0.078 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.416 0.044 0.079 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[0, 0]]) selected_action: tensor([0]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 116 lasted for 129 time steps with total reward of 128.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.047 -0.004 -0.015 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.051 -0.008 -0.008 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.058 -0.012 0.004 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.07 -0.008 0.022 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.077 -0.012 0.034 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.089 -0.008 0.052 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.097 -0.012 0.064 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.108 -0.016 0.083 0.025 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.124 -0.012 0.108 0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.136 -0.008 0.127 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.143 -0.012 0.142 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.155 -0.008 0.163 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.163 -0.004 0.179 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.167 -0.0 0.19 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.167 0.004 0.197 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.163 0.008 0.199 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.156 0.011 0.197 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.144 0.015 0.19 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.129 0.019 0.179 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.11 0.023 0.163 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.087 0.027 0.142 -0.025 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.061 0.031 0.117 -0.03 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.03 0.027 0.087 -0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.003 0.031 0.063 -0.029 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.027 0.027 0.034 -0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.054 0.031 0.012 -0.028 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.084 0.027 -0.017 -0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.111 0.023 -0.039 -0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.134 0.019 -0.056 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.153 0.015 -0.067 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.167 0.011 -0.072 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.179 0.007 -0.072 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.186 0.003 -0.067 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.189 -0.001 -0.056 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.188 -0.004 -0.04 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.184 -0.008 -0.018 0.027 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.176 -0.012 0.009 0.033 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.163 -0.008 0.042 0.027 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.155 -0.012 0.069 0.033 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.143 -0.008 0.102 0.028 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.134 -0.005 0.13 0.023 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.13 -0.008 0.152 0.029 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.121 -0.005 0.182 0.024 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.117 -0.001 0.206 0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.116 0.003 0.226 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[12, 16]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 117 lasted for 46 time steps with total reward of 45.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.03 -0.004 0.0 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.026 -0.008 0.007 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.017 -0.012 0.019 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.005 -0.008 0.038 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.003 -0.012 0.051 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.015 -0.008 0.07 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.024 -0.012 0.083 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.036 -0.008 0.103 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.044 -0.005 0.117 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.049 -0.001 0.126 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.05 -0.005 0.13 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.054 -0.001 0.141 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.055 0.003 0.146 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.052 0.007 0.147 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.045 0.003 0.143 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.042 0.007 0.145 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.035 0.011 0.143 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.024 0.007 0.136 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.018 0.011 0.135 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.007 0.015 0.13 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.008 0.011 0.12 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.018 0.014 0.116 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.033 0.018 0.107 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.051 0.014 0.093 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.065 0.018 0.086 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.084 0.022 0.073 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.106 0.018 0.055 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.124 0.022 0.044 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.146 0.018 0.027 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.164 0.022 0.016 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.186 0.018 -0.001 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.204 0.014 -0.012 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.219 0.01 -0.017 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.229 0.006 -0.016 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.236 0.003 -0.009 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.238 -0.001 0.003 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.237 -0.005 0.021 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.232 -0.001 0.045 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.23 -0.005 0.064 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.225 -0.001 0.088 0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.224 0.003 0.107 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.226 -0.001 0.121 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.225 0.002 0.141 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.227 0.006 0.156 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.234 0.002 0.167 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.236 0.006 0.184 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.242 0.01 0.196 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.252 0.014 0.204 0.003 output tensor([[12, 16]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.266 0.018 0.207 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.284 0.022 0.206 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.305 0.025 0.2 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.331 0.029 0.19 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.36 0.033 0.176 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.393 0.029 0.157 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.422 0.033 0.144 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.455 0.037 0.127 -0.022 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.492 0.033 0.105 -0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.525 0.029 0.09 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.554 0.033 0.081 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.587 0.029 0.067 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.616 0.033 0.059 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.649 0.029 0.046 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.678 0.033 0.039 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.71 0.029 0.027 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.739 0.025 0.021 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.764 0.021 0.02 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.785 0.025 0.026 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.81 0.021 0.026 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.831 0.017 0.032 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.849 0.021 0.043 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.87 0.017 0.05 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.887 0.021 0.062 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.908 0.017 0.069 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.925 0.021 0.082 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.946 0.017 0.09 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.963 0.021 0.104 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.984 0.017 0.112 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.001 0.021 0.128 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.022 0.025 0.138 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.046 0.029 0.143 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.075 0.032 0.143 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.107 0.029 0.138 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.136 0.032 0.14 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.168 0.036 0.137 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.205 0.04 0.13 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.245 0.044 0.117 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.289 0.04 0.099 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.329 0.044 0.088 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.372 0.04 0.072 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.412 0.044 0.062 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.456 0.04 0.046 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.496 0.044 0.037 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.54 0.04 0.022 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.58 0.036 0.014 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.616 0.032 0.011 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.648 0.036 0.014 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.684 0.032 0.012 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.716 0.028 0.015 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.744 0.032 0.024 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.776 0.028 0.028 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.804 0.024 0.038 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.829 0.028 0.053 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.857 0.024 0.063 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.881 0.02 0.08 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.901 0.024 0.102 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.926 0.028 0.119 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.954 0.032 0.131 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.986 0.036 0.138 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.021 0.032 0.14 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.053 0.036 0.148 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.089 0.04 0.152 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.128 0.043 0.151 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.172 0.039 0.145 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.211 0.043 0.145 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.255 0.047 0.141 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.302 0.051 0.132 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.353 0.047 0.118 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.4 0.051 0.111 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[0, 0]]) selected_action: tensor([0]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 118 lasted for 119 time steps with total reward of 118.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.025 -0.004 -0.028 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.021 -0.007 -0.023 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.014 -0.011 -0.013 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.003 -0.007 0.004 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.005 -0.011 0.014 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.016 -0.015 0.03 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.032 -0.011 0.052 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.043 -0.015 0.068 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.058 -0.011 0.09 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.069 -0.015 0.108 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.085 -0.011 0.131 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.096 -0.008 0.149 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.104 -0.004 0.163 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.108 0.0 0.171 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.107 -0.004 0.175 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.111 0.0 0.185 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.111 0.004 0.191 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.107 0.008 0.193 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.1 0.012 0.19 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.088 0.015 0.182 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.073 0.019 0.17 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.053 0.015 0.153 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.038 0.019 0.143 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.019 0.023 0.128 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.004 0.019 0.108 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.023 0.023 0.095 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.046 0.019 0.077 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.065 0.023 0.065 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.088 0.019 0.047 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.107 0.015 0.036 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.122 0.019 0.032 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.141 0.015 0.021 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.156 0.011 0.017 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.167 0.015 0.018 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.182 0.011 0.014 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.193 0.007 0.016 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.201 0.003 0.024 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.204 0.007 0.037 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.211 0.003 0.045 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.215 0.007 0.059 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.222 0.003 0.068 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.225 0.007 0.082 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.232 0.011 0.092 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.243 0.007 0.096 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.25 0.011 0.106 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.261 0.015 0.111 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.276 0.011 0.111 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.287 0.015 0.118 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.302 0.019 0.119 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.32 0.015 0.116 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.335 0.019 0.119 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.354 0.022 0.116 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.376 0.019 0.109 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.395 0.022 0.108 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.417 0.018 0.103 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.436 0.022 0.103 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.458 0.026 0.099 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.484 0.022 0.089 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.506 0.026 0.086 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.533 0.022 0.077 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.555 0.026 0.075 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.581 0.022 0.068 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.603 0.026 0.067 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.629 0.022 0.06 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.651 0.018 0.06 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.669 0.022 0.066 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.692 0.026 0.066 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.718 0.022 0.061 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.74 0.026 0.062 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.766 0.022 0.058 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.788 0.026 0.06 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.814 0.022 0.057 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.836 0.026 0.06 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.861 0.022 0.057 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.883 0.026 0.061 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.909 0.022 0.059 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.931 0.026 0.063 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.957 0.022 0.062 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.979 0.026 0.067 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.005 0.022 0.066 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.026 0.026 0.072 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.052 0.022 0.073 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.074 0.026 0.079 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.1 0.022 0.081 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.122 0.026 0.088 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.147 0.022 0.091 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.169 0.026 0.099 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.195 0.029 0.103 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.224 0.033 0.101 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.257 0.029 0.094 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.287 0.033 0.094 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.32 0.037 0.088 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.357 0.033 0.077 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.39 0.037 0.073 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.428 0.041 0.063 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.469 0.037 0.048 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.506 0.041 0.039 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.547 0.037 0.024 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.584 0.033 0.016 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.617 0.029 0.013 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.646 0.033 0.017 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.679 0.029 0.014 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.708 0.025 0.018 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.734 0.029 0.028 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.763 0.025 0.032 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.788 0.029 0.041 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.818 0.025 0.046 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.843 0.021 0.056 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.864 0.025 0.073 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.889 0.029 0.084 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.919 0.025 0.089 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.944 0.029 0.101 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.973 0.033 0.108 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.006 0.029 0.109 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.035 0.033 0.117 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.068 0.037 0.12 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.105 0.033 0.118 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.137 0.037 0.123 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.174 0.033 0.122 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.207 0.037 0.128 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.244 0.04 0.129 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.284 0.044 0.125 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.328 0.048 0.115 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.377 0.044 0.101 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.421 0.048 0.094 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[0, 0]]) selected_action: tensor([0]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 119 lasted for 126 time steps with total reward of 125.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.031 -0.004 0.028 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.034 -0.007 0.033 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.042 -0.004 0.044 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.045 -0.008 0.05 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.053 -0.004 0.062 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.057 -0.008 0.068 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.064 -0.004 0.08 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.068 0.0 0.087 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.068 -0.004 0.089 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.071 0.0 0.097 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.071 -0.004 0.1 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.075 0.0 0.109 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.075 0.004 0.113 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.071 0.0 0.112 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.071 0.004 0.117 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.067 0.008 0.118 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.059 0.004 0.113 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.055 0.008 0.115 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.047 0.012 0.111 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.036 0.015 0.103 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.02 0.012 0.089 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.009 0.008 0.082 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.001 0.011 0.082 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.01 0.008 0.076 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.018 0.011 0.076 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.029 0.015 0.071 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.044 0.011 0.061 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.056 0.007 0.057 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.063 0.011 0.059 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.075 0.007 0.055 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.082 0.011 0.058 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.093 0.015 0.056 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.109 0.011 0.048 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.12 0.007 0.046 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.127 0.011 0.05 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.139 0.007 0.049 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.146 0.003 0.053 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.149 0.007 0.064 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.157 0.003 0.07 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.16 0.007 0.082 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.167 0.003 0.088 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.171 0.007 0.101 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.178 0.003 0.108 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.181 0.007 0.122 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.188 0.011 0.131 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.199 0.007 0.135 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.206 0.011 0.145 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.217 0.015 0.15 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.232 0.019 0.151 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.251 0.023 0.146 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.273 0.019 0.137 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.292 0.022 0.135 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.314 0.019 0.127 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.333 0.022 0.127 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.355 0.026 0.121 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.382 0.022 0.11 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.404 0.026 0.106 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.43 0.03 0.097 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.46 0.026 0.082 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.486 0.03 0.074 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.516 0.034 0.061 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.55 0.03 0.042 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.58 0.034 0.029 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.614 0.03 0.011 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.644 0.026 -0.001 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.67 0.03 -0.007 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.7 0.026 -0.019 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.726 0.022 -0.025 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.748 0.018 -0.025 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.766 0.014 -0.02 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.78 0.01 -0.009 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.791 0.014 0.007 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.805 0.01 0.018 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.816 0.007 0.035 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.822 0.01 0.057 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.833 0.007 0.074 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.839 0.01 0.098 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.85 0.006 0.115 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.856 0.01 0.14 0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.866 0.014 0.159 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.881 0.018 0.173 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.899 0.014 0.183 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.913 0.018 0.199 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.931 0.022 0.211 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 120 lasted for 85 time steps with total reward of 84.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.047 -0.004 0.032 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.043 -0.008 0.038 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.035 -0.004 0.05 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.031 -0.0 0.056 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.03 -0.004 0.057 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.026 -0.008 0.065 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.018 -0.004 0.078 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.014 -0.0 0.086 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.014 -0.004 0.088 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.01 -0.0 0.097 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.01 0.004 0.101 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.013 -0.0 0.1 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.013 0.004 0.104 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.016 -0.0 0.104 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.016 0.003 0.11 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.019 -0.0 0.111 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.019 0.003 0.119 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.022 0.007 0.121 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.03 0.003 0.119 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.033 0.007 0.123 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.04 0.011 0.122 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.051 0.007 0.116 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.059 0.011 0.116 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.07 0.015 0.111 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.084 0.011 0.102 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.095 0.015 0.098 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.11 0.019 0.09 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.129 0.015 0.076 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.144 0.019 0.069 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.162 0.015 0.057 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.177 0.019 0.05 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.196 0.015 0.039 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.21 0.019 0.033 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.229 0.015 0.022 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.244 0.011 0.017 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.254 0.015 0.018 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.269 0.011 0.013 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.28 0.007 0.014 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.287 0.011 0.021 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.297 0.007 0.022 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.304 0.011 0.029 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.315 0.007 0.031 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.322 0.003 0.038 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.325 0.007 0.052 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.331 0.003 0.06 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.334 0.007 0.074 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.341 0.011 0.083 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.352 0.007 0.086 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.358 0.011 0.096 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.369 0.007 0.1 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.376 0.011 0.111 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.386 0.007 0.116 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.393 0.01 0.128 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.403 0.014 0.135 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.418 0.018 0.137 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.436 0.022 0.135 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.458 0.018 0.127 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.476 0.022 0.126 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.498 0.026 0.119 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.524 0.022 0.108 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.546 0.026 0.103 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.572 0.03 0.094 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.601 0.026 0.079 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.627 0.03 0.07 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.657 0.026 0.056 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.682 0.022 0.049 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.704 0.026 0.047 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.73 0.022 0.04 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.752 0.026 0.04 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.777 0.022 0.033 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.799 0.018 0.033 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.817 0.014 0.039 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.831 0.018 0.05 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.848 0.014 0.057 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.862 0.018 0.069 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.88 0.014 0.076 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.894 0.018 0.089 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.912 0.022 0.097 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.933 0.018 0.099 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.951 0.022 0.108 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.972 0.018 0.112 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.99 0.021 0.123 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.011 0.025 0.128 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.037 0.029 0.128 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.066 0.025 0.123 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.091 0.029 0.125 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.12 0.033 0.121 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.153 0.029 0.113 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.182 0.033 0.111 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.215 0.037 0.105 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.252 0.033 0.093 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.285 0.037 0.087 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.322 0.033 0.076 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.355 0.037 0.072 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.391 0.033 0.062 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.424 0.037 0.059 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.461 0.033 0.05 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.494 0.037 0.047 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.53 0.033 0.039 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.563 0.029 0.037 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.592 0.033 0.041 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.624 0.029 0.04 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.653 0.033 0.044 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.686 0.029 0.043 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.715 0.033 0.048 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.747 0.029 0.048 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.776 0.033 0.054 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.809 0.029 0.054 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.837 0.033 0.06 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.87 0.029 0.061 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.898 0.033 0.068 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.931 0.036 0.07 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.967 0.033 0.066 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.0 0.036 0.068 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.036 0.032 0.065 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.069 0.036 0.068 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.105 0.032 0.066 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.138 0.036 0.07 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.174 0.032 0.069 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.206 0.036 0.074 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.243 0.032 0.074 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.275 0.036 0.08 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.311 0.032 0.08 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.344 0.036 0.087 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.38 0.04 0.089 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.42 0.036 0.085 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 121 lasted for 127 time steps with total reward of 126.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.046 -0.003 -0.026 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.042 -0.007 -0.021 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.035 -0.003 -0.011 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.032 -0.007 -0.006 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.025 -0.011 0.004 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.014 -0.015 0.02 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.001 -0.011 0.042 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.012 -0.015 0.058 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.027 -0.011 0.08 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.038 -0.015 0.097 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.052 -0.011 0.12 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.064 -0.007 0.138 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.071 -0.011 0.151 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.082 -0.007 0.17 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.089 -0.003 0.185 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.092 0.0 0.195 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.092 0.004 0.201 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.088 0.008 0.201 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.08 0.004 0.198 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.076 0.008 0.201 -0.001 output tensor([[12, 16]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.068 0.012 0.2 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.056 0.016 0.195 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.04 0.012 0.185 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.028 0.016 0.182 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.013 0.019 0.174 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.007 0.023 0.162 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.03 0.019 0.145 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.049 0.023 0.135 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.072 0.027 0.12 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.099 0.023 0.1 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.123 0.027 0.086 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.149 0.023 0.068 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.173 0.027 0.055 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.199 0.023 0.038 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.222 0.027 0.026 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.249 0.023 0.009 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.272 0.019 -0.002 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.291 0.015 -0.007 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.307 0.011 -0.006 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.318 0.007 0.0 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.325 0.003 0.012 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.329 0.007 0.031 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.336 0.003 0.043 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.34 0.007 0.061 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.347 0.011 0.074 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.358 0.007 0.082 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.366 0.011 0.095 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.377 0.007 0.104 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.384 0.011 0.119 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.395 0.015 0.128 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.41 0.011 0.133 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.421 0.015 0.144 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.436 0.019 0.15 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.455 0.023 0.152 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.478 0.027 0.148 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.504 0.023 0.14 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.527 0.026 0.138 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.553 0.03 0.132 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.584 0.026 0.12 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.61 0.03 0.115 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.64 0.026 0.105 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.666 0.03 0.102 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.697 0.034 0.094 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.731 0.03 0.08 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.761 0.034 0.073 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.795 0.03 0.06 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.825 0.034 0.054 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.859 0.03 0.042 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.889 0.034 0.037 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.923 0.03 0.025 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.953 0.026 0.02 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.979 0.03 0.021 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.009 0.026 0.017 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.035 0.022 0.018 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.057 0.026 0.025 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.083 0.022 0.026 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.105 0.018 0.034 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.123 0.022 0.047 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.145 0.018 0.055 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.164 0.022 0.069 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.186 0.018 0.077 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.204 0.022 0.092 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.226 0.026 0.102 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.252 0.022 0.106 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.274 0.026 0.116 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.3 0.03 0.122 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.33 0.026 0.122 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.355 0.03 0.129 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.385 0.034 0.131 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.419 0.037 0.128 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.456 0.041 0.12 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.497 0.037 0.107 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.535 0.041 0.1 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.576 0.037 0.088 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.613 0.041 0.083 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.654 0.037 0.073 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.692 0.041 0.069 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.733 0.037 0.059 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.77 0.041 0.056 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.811 0.037 0.047 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.848 0.041 0.045 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.889 0.037 0.037 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.926 0.033 0.035 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.959 0.037 0.039 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.997 0.033 0.038 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.03 0.029 0.042 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.059 0.033 0.053 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.092 0.037 0.058 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.129 0.033 0.058 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.162 0.029 0.063 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.192 0.033 0.075 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.225 0.029 0.082 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.254 0.033 0.095 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.287 0.029 0.103 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.316 0.033 0.117 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.349 0.029 0.125 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.378 0.033 0.141 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.411 0.037 0.151 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 122 lasted for 119 time steps with total reward of 118.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.014 -0.003 0.003 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.017 -0.007 0.008 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.024 -0.003 0.02 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.028 -0.007 0.026 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.035 -0.003 0.038 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.038 -0.007 0.044 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.045 -0.011 0.056 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.056 -0.007 0.074 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.063 -0.003 0.087 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.067 -0.007 0.095 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.074 -0.003 0.108 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.077 -0.007 0.117 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.085 -0.003 0.132 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.088 0.0 0.142 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.087 -0.003 0.147 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.091 0.0 0.159 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.091 0.004 0.166 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.086 0.008 0.168 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.078 0.012 0.166 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.066 0.016 0.158 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.051 0.02 0.146 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.031 0.016 0.129 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.015 0.02 0.119 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.004 0.023 0.104 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.028 0.019 0.084 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.047 0.016 0.07 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.063 0.019 0.063 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.082 0.023 0.05 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.105 0.019 0.032 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.125 0.016 0.02 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.14 0.012 0.014 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.152 0.008 0.014 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.16 0.004 0.02 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.163 0.008 0.032 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.171 0.004 0.038 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.175 0.008 0.051 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.183 0.004 0.057 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.186 0.008 0.07 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.194 0.004 0.077 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.198 0.008 0.091 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.205 0.004 0.099 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.209 0.008 0.114 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.216 0.004 0.123 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.22 0.007 0.139 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.227 0.011 0.15 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.239 0.015 0.156 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.254 0.019 0.157 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.273 0.023 0.154 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.296 0.027 0.145 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.323 0.031 0.132 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.353 0.027 0.114 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.38 0.031 0.103 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.41 0.027 0.086 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.437 0.03 0.076 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.467 0.027 0.061 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.494 0.03 0.052 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.524 0.027 0.037 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.551 0.03 0.029 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.581 0.027 0.015 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.608 0.023 0.007 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.63 0.019 0.005 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.649 0.015 0.009 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.664 0.011 0.019 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.675 0.015 0.035 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.69 0.011 0.045 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.7 0.007 0.061 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.707 0.011 0.083 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.718 0.007 0.099 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.725 0.011 0.123 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.736 0.015 0.14 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.751 0.019 0.153 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.769 0.022 0.161 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.791 0.018 0.164 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.81 0.022 0.174 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.832 0.026 0.179 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.858 0.03 0.18 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.888 0.034 0.176 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.922 0.038 0.167 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.96 0.041 0.154 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.001 0.038 0.136 -0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.039 0.041 0.124 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.08 0.037 0.108 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.118 0.041 0.098 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.159 0.037 0.083 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.196 0.041 0.075 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.238 0.037 0.061 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.275 0.041 0.054 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.316 0.037 0.041 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.354 0.041 0.034 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.395 0.037 0.022 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.432 0.033 0.015 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.466 0.037 0.015 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.503 0.033 0.009 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.537 0.03 0.009 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.566 0.026 0.015 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.592 0.03 0.027 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.621 0.026 0.033 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.647 0.022 0.045 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.668 0.026 0.063 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.694 0.029 0.075 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.724 0.026 0.082 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.749 0.029 0.096 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.778 0.025 0.104 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.804 0.029 0.118 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.833 0.033 0.128 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.867 0.037 0.132 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.904 0.033 0.131 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.937 0.037 0.137 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.974 0.041 0.138 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.015 0.045 0.134 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.059 0.041 0.125 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.1 0.045 0.123 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.145 0.049 0.115 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.193 0.045 0.103 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.238 0.048 0.097 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.286 0.045 0.086 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.331 0.048 0.082 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.379 0.044 0.072 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.424 0.048 0.068 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[0, 0]]) selected_action: tensor([0]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 123 lasted for 120 time steps with total reward of 119.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.019 -0.004 0.042 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.015 -0.008 0.048 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.007 -0.004 0.06 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.003 -0.008 0.067 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.005 -0.004 0.08 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.009 -0.008 0.088 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.017 -0.004 0.102 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.021 -0.008 0.11 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.029 -0.004 0.125 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.034 -0.0 0.135 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.034 0.003 0.14 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.031 -0.0 0.14 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.031 0.003 0.147 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.028 0.007 0.148 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.02 0.011 0.145 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.009 0.015 0.137 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.006 0.011 0.124 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.017 0.015 0.118 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.032 0.011 0.107 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.043 0.015 0.102 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.057 0.011 0.093 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.068 0.015 0.089 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.083 0.019 0.081 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.102 0.015 0.067 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.116 0.019 0.059 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.135 0.015 0.046 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.15 0.019 0.04 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.168 0.015 0.027 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.183 0.019 0.021 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.201 0.015 0.009 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.216 0.011 0.003 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.227 0.007 0.003 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.234 0.011 0.009 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.244 0.007 0.009 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.251 0.003 0.015 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.254 0.007 0.027 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.261 0.003 0.033 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.264 -0.001 0.046 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.263 0.003 0.064 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.266 -0.001 0.076 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.265 0.003 0.095 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.268 -0.001 0.109 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.266 0.003 0.129 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.269 0.007 0.144 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.276 0.011 0.154 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.286 0.007 0.159 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.293 0.01 0.17 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.303 0.014 0.177 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.318 0.018 0.179 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.336 0.022 0.177 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.358 0.026 0.17 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.384 0.022 0.158 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.405 0.026 0.153 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.431 0.03 0.144 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.461 0.026 0.129 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.486 0.029 0.122 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.516 0.026 0.109 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.541 0.029 0.103 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.571 0.033 0.091 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.604 0.029 0.075 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.634 0.033 0.065 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.667 0.029 0.049 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.696 0.025 0.04 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.722 0.029 0.037 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.751 0.025 0.029 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.776 0.021 0.026 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.798 0.018 0.03 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.815 0.021 0.039 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.837 0.018 0.043 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.854 0.021 0.053 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.876 0.018 0.057 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.893 0.021 0.068 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.915 0.017 0.073 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.932 0.021 0.084 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.954 0.025 0.09 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.979 0.021 0.091 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.0 0.025 0.098 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.026 0.029 0.1 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.055 0.033 0.096 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.088 0.029 0.088 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.117 0.033 0.085 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.149 0.029 0.078 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.178 0.033 0.077 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.211 0.029 0.07 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.24 0.033 0.07 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.273 0.029 0.065 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.302 0.033 0.065 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.335 0.029 0.061 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.364 0.033 0.062 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.396 0.037 0.059 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.433 0.033 0.049 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.466 0.029 0.046 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.494 0.033 0.049 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.527 0.029 0.047 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.556 0.033 0.05 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.588 0.029 0.048 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.617 0.033 0.053 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.65 0.029 0.051 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.678 0.033 0.056 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.711 0.029 0.056 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.74 0.025 0.061 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.765 0.029 0.073 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.793 0.033 0.079 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.826 0.029 0.08 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.854 0.032 0.087 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.887 0.036 0.089 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.923 0.04 0.086 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.963 0.036 0.077 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.0 0.04 0.075 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.04 0.036 0.068 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.076 0.032 0.066 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.108 0.036 0.071 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.145 0.04 0.071 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.185 0.036 0.065 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.221 0.04 0.066 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.261 0.036 0.061 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.297 0.04 0.062 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.337 0.036 0.058 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.373 0.032 0.06 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.405 0.036 0.068 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "output tensor([[0, 0]]) selected_action: tensor([0]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 124 lasted for 121 time steps with total reward of 120.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.034 -0.003 -0.041 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.037 -0.007 -0.036 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.044 -0.011 -0.026 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.054 -0.007 -0.01 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.061 -0.011 -0.0 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.072 -0.015 0.015 0.021 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.087 -0.011 0.037 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.098 -0.015 0.052 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.112 -0.011 0.074 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.123 -0.015 0.09 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.138 -0.011 0.113 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.149 -0.007 0.13 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.156 -0.011 0.142 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.167 -0.007 0.161 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.174 -0.003 0.175 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.177 0.001 0.184 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.177 0.004 0.189 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.172 0.008 0.189 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.164 0.012 0.184 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.152 0.008 0.175 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.144 0.012 0.173 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.132 0.016 0.166 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.116 0.02 0.154 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.096 0.024 0.138 -0.021 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.073 0.02 0.117 -0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.053 0.023 0.102 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.029 0.02 0.083 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.01 0.023 0.07 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.014 0.02 0.051 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.033 0.023 0.039 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.057 0.02 0.021 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.076 0.016 0.01 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.092 0.019 0.004 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.111 0.016 -0.007 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.127 0.012 -0.013 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.138 0.016 -0.012 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.154 0.012 -0.018 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.166 0.008 -0.018 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.174 0.004 -0.012 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.177 0.0 -0.0 0.017 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.177 0.004 0.017 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.181 0.0 0.029 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.181 0.004 0.046 0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.185 -0.0 0.058 0.018 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.185 0.004 0.076 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.189 -0.0 0.089 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.189 0.004 0.108 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.193 0.008 0.121 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.201 0.004 0.13 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.204 0.008 0.145 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.212 0.011 0.155 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.223 0.015 0.16 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.239 0.019 0.16 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.258 0.015 0.156 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.273 0.019 0.158 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.292 0.023 0.156 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.315 0.027 0.148 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.342 0.031 0.136 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.373 0.027 0.12 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.399 0.031 0.109 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.43 0.027 0.094 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.457 0.023 0.085 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.479 0.027 0.083 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.506 0.023 0.075 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.529 0.027 0.074 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.555 0.023 0.067 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.578 0.027 0.067 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.604 0.023 0.061 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.627 0.026 0.062 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.653 0.023 0.057 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.676 0.026 0.058 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.702 0.023 0.054 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.725 0.026 0.056 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.751 0.022 0.052 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.774 0.026 0.055 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.8 0.022 0.052 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.823 0.019 0.055 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.841 0.022 0.065 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.864 0.019 0.069 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.882 0.022 0.079 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.905 0.026 0.084 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.931 0.022 0.084 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.953 0.026 0.09 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.979 0.022 0.09 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.002 0.026 0.097 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.028 0.03 0.099 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.058 0.026 0.095 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.084 0.03 0.098 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.114 0.026 0.096 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.14 0.03 0.1 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.17 0.026 0.099 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.196 0.03 0.105 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.226 0.026 0.105 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.252 0.03 0.111 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.282 0.034 0.113 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.315 0.03 0.109 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.345 0.034 0.112 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.379 0.037 0.11 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.416 0.034 0.103 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.45 0.037 0.102 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.487 0.034 0.096 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.521 0.037 0.097 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.558 0.033 0.092 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.592 0.037 0.094 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.629 0.041 0.09 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.67 0.037 0.081 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.707 0.041 0.079 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.749 0.045 0.071 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.794 0.041 0.058 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.835 0.045 0.051 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.88 0.041 0.039 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.921 0.045 0.033 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.966 0.041 0.022 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.007 0.037 0.016 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.044 0.041 0.016 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.085 0.037 0.011 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.122 0.041 0.012 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.163 0.037 0.006 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.2 0.033 0.007 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.233 0.029 0.014 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.263 0.033 0.026 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.296 0.029 0.033 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.325 0.025 0.046 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.351 0.029 0.065 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.38 0.033 0.078 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.413 0.029 0.086 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 125 lasted for 127 time steps with total reward of 126.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.025 -0.004 0.041 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.029 -0.008 0.048 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.037 -0.004 0.061 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.041 -0.008 0.069 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.049 -0.004 0.082 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.053 -0.008 0.091 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.061 -0.004 0.105 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.065 -0.0 0.115 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.065 -0.004 0.119 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.07 -0.0 0.13 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.07 -0.004 0.135 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.074 -0.0 0.148 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.075 0.003 0.155 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.072 0.007 0.158 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.064 0.011 0.155 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.053 0.007 0.148 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.046 0.011 0.148 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.035 0.015 0.143 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.02 0.019 0.133 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.001 0.015 0.118 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.013 0.019 0.11 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.032 0.015 0.096 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.047 0.019 0.089 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.065 0.015 0.077 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.08 0.019 0.072 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.099 0.022 0.061 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.121 0.019 0.044 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.14 0.015 0.034 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.154 0.018 0.03 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.173 0.015 0.02 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.187 0.018 0.017 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.206 0.015 0.007 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.22 0.011 0.004 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.231 0.007 0.006 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.238 0.003 0.015 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.241 0.007 0.029 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.247 0.003 0.037 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.25 0.007 0.052 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.257 0.003 0.061 0.015 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.26 0.007 0.076 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.266 0.003 0.085 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.269 0.007 0.101 0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.276 0.011 0.112 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.286 0.007 0.117 0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.293 0.01 0.129 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.304 0.014 0.136 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.318 0.01 0.138 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.328 0.014 0.147 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.342 0.018 0.15 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.361 0.014 0.149 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.375 0.018 0.155 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.393 0.022 0.155 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.415 0.018 0.151 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.433 0.022 0.154 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.454 0.026 0.151 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.48 0.029 0.144 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.51 0.026 0.133 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.535 0.029 0.127 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.565 0.025 0.117 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.59 0.029 0.114 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.619 0.033 0.105 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.653 0.029 0.091 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.682 0.033 0.084 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.715 0.037 0.072 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.752 0.033 0.054 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.785 0.029 0.042 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.814 0.025 0.037 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.84 0.029 0.038 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.869 0.025 0.033 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.894 0.029 0.034 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.923 0.025 0.03 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.949 0.021 0.032 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.97 0.025 0.039 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.995 0.021 0.041 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.016 0.025 0.049 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.042 0.021 0.052 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.063 0.025 0.061 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.088 0.021 0.064 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.109 0.025 0.073 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.135 0.021 0.077 0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.156 0.025 0.088 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.181 0.021 0.093 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.202 0.025 0.104 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.227 0.021 0.11 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.248 0.025 0.123 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.273 0.021 0.13 0.014 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.294 0.025 0.144 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.319 0.029 0.153 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.348 0.033 0.157 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.381 0.036 0.157 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.417 0.033 0.151 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.45 0.036 0.153 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.486 0.04 0.149 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.526 0.036 0.141 -0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.563 0.04 0.139 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.603 0.044 0.133 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.647 0.04 0.121 -0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.687 0.044 0.117 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.731 0.048 0.107 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.779 0.044 0.092 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.823 0.048 0.084 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.87 0.044 0.07 -0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.914 0.048 0.063 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.962 0.044 0.05 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.006 0.04 0.043 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.046 0.036 0.043 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.082 0.04 0.049 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.121 0.044 0.049 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.165 0.04 0.044 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.205 0.044 0.045 -0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.249 0.04 0.04 0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.289 0.044 0.041 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.332 0.04 0.037 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.372 0.044 0.039 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.416 0.04 0.035 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "output tensor([[0, 0]]) selected_action: tensor([0]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 126 lasted for 116 time steps with total reward of 115.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.03 -0.004 -0.039 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.026 -0.008 -0.034 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.019 -0.011 -0.023 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.007 -0.008 -0.007 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.0 -0.011 0.004 0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.012 -0.015 0.02 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.027 -0.011 0.042 0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.038 -0.015 0.058 0.022 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.054 -0.011 0.08 0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.065 -0.015 0.097 0.023 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.081 -0.012 0.12 0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.092 -0.008 0.138 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.1 -0.012 0.151 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.111 -0.008 0.17 0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.119 -0.004 0.185 0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.123 -0.0 0.195 0.005 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.123 0.004 0.201 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.119 0.008 0.202 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.112 0.011 0.198 -0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.1 0.015 0.19 -0.012 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.085 0.019 0.178 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.066 0.015 0.161 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.05 0.019 0.151 -0.015 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.031 0.023 0.136 -0.02 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.009 0.019 0.116 -0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.01 0.023 0.103 -0.018 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.033 0.019 0.085 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.052 0.023 0.073 -0.017 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.075 0.027 0.056 -0.022 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.102 0.023 0.033 -0.016 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.124 0.019 0.017 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.143 0.023 0.007 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.166 0.019 -0.009 -0.01 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.185 0.015 -0.019 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.2 0.011 -0.023 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.211 0.007 -0.022 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.218 0.011 -0.014 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.229 0.007 -0.013 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.236 0.003 -0.006 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.239 -0.001 0.007 0.019 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.239 -0.005 0.025 0.024 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.234 -0.001 0.05 0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.233 0.003 0.069 0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.237 -0.001 0.082 0.02 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.236 0.003 0.102 0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.239 0.007 0.116 0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.246 0.011 0.125 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.257 0.007 0.129 0.011 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.264 0.011 0.139 0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.275 0.015 0.145 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.29 0.019 0.146 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.308 0.015 0.141 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.323 0.018 0.144 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.341 0.022 0.141 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.364 0.018 0.134 -0.001 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.382 0.022 0.133 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.404 0.026 0.128 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.431 0.03 0.117 -0.016 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.461 0.026 0.102 -0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.487 0.03 0.093 -0.014 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.517 0.026 0.078 -0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.543 0.03 0.071 -0.013 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.572 0.034 0.058 -0.019 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.606 0.03 0.039 -0.012 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.636 0.026 0.027 -0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.662 0.022 0.021 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.684 0.018 0.02 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.702 0.022 0.026 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.724 0.026 0.026 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.75 0.022 0.021 0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.772 0.018 0.021 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.79 0.022 0.027 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.812 0.018 0.028 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.83 0.014 0.035 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.844 0.018 0.048 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.862 0.022 0.055 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.884 0.018 0.056 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.902 0.022 0.064 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.924 0.018 0.066 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.942 0.022 0.075 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.964 0.018 0.078 0.009 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.982 0.022 0.087 0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.004 0.026 0.091 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.03 0.022 0.09 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.052 0.026 0.095 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.077 0.022 0.095 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.099 0.026 0.101 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.125 0.029 0.102 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.154 0.026 0.098 0.002 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.18 0.029 0.1 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.209 0.025 0.098 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.234 0.029 0.101 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.264 0.033 0.1 -0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.297 0.029 0.093 -0.0 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.326 0.033 0.092 -0.006 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.36 0.037 0.087 -0.011 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.397 0.033 0.076 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.43 0.037 0.072 -0.01 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.467 0.033 0.062 -0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.5 0.037 0.058 -0.009 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.537 0.033 0.049 -0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.57 0.029 0.047 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.599 0.033 0.05 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.632 0.029 0.048 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.661 0.033 0.052 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.694 0.029 0.05 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.723 0.033 0.055 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.756 0.029 0.054 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.785 0.033 0.059 -0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.818 0.029 0.059 0.006 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.847 0.033 0.065 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.88 0.029 0.066 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.909 0.033 0.072 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.942 0.029 0.074 0.008 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 1.971 0.033 0.081 0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.004 0.037 0.084 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.04 0.033 0.081 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.073 0.037 0.084 -0.002 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.11 0.033 0.082 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.143 0.037 0.086 -0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.179 0.033 0.085 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.212 0.037 0.091 0.0 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.248 0.033 0.091 0.007 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.281 0.037 0.098 0.001 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.318 0.04 0.099 -0.004 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.358 0.036 0.095 0.003 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.394 0.04 0.097 -0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): 2.435 0.036 0.095 0.004 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "output tensor([[6, 8]]) selected_action: tensor([1]) rew: 0.0\n",
            "\n",
            "Episode not successful!\n",
            "\n",
            "Episode 127 lasted for 129 time steps with total reward of 128.0\n",
            "\n",
            "state (x, x_dot, theta (rad), theta_dot): 0.045 -0.003 -0.0 0.005 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
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            "state (x, x_dot, theta (rad), theta_dot): -0.012 -0.003 0.091 0.007 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.016 -0.007 0.098 0.013 output tensor([[0, 0]]) selected_action: tensor([0]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.023 -0.003 0.111 0.008 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n",
            "state (x, x_dot, theta (rad), theta_dot): -0.026 0.001 0.119 0.003 output tensor([[6, 8]]) selected_action: tensor([1]) rew: 1.0\n"
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      "source": [
        "manual_seed(SEED)\n",
        "\n",
        "\n",
        "net = FCSNN(**network_hparams)\n",
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