RLjs currently serves as an interactive playground for learning reinforcement learning.
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Updated
Jan 7, 2019 - JavaScript
RLjs currently serves as an interactive playground for learning reinforcement learning.
Navigation Project - Udacity Deep Reinforcement Learning Nanodegree
Reinforcement learning algorithms
This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch
Implementation of RL algorithms to beat Atari 2600 games
Implementation notebooks and scripts of Deep Reinforcement learning Algorithms in PyTorch and TensorFlow.
Training RL agent to master Facebook TetrisBattle--PyTorch implementation
This is a repository for Coursera Reinforcement Learning Course Notebook ,, these consist of my solutions. Feel Free to take a look , if you are stuck in Course and suggest corrections, if you find any mistake. Also Useful if you are looking for an implementation of RL-Algorithms. ** NOTE THESE NOTEBOOKS DON'T WORK AS THEY DO NOT CONTAIN UTILITY…
Code for some fun exercises in the textbook 'Reinforcement Learning - An Introduction'
Various RL algorithms implementations
This repository contains my implementations of well-known reinforcement learning algorithms for training a single agent. All implementations are done using PyTorch and Python >=3.6.
This repository has RL algorithms implemented using python
Toy case for learning through Reinforcement Learning algorithms how to establish TCP connections.
Implémentations d'apprentissage par renforcement mixées avec des techniques de Deep Learning sur des environnements OpenAI Gym
Reinforcement Learning framework for learning IoT interactions.
Safe Reinforce Learning -> Constraint algorithms to train agents in Safety Gym, paper notes on research papers regarding RL with constraints + optimizer + neural networks, PyTorch implementation on policy gradient algorithms
Deep Reinforcement Learning - Implementations and Theory: A path to mastery
self-studying the Sutton & Barto the hard way
This is the repository for Offline-Online Representation Learning for Reinforcement Learning.
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