deep_reinforcement_learning_in_action

• deep_reinforcement_learning_in_action
  • Requirements
    • gcc-9
    • gym
  • Build
  • Examples
    • Deep Q-learning for grid world
    • Policy gradient for CartPole problem
      • Start gym
      • Start policy gradient

Self-brewed code from the Deep Reinforcement Learning in Action book from Manning, Inc

Requirements

gcc-9

Install gcc-9:

sudo add-apt-repository ppa:ubuntu-toolchain-r/test
sudo apt update
sudo apt install gcc-9

Set gcc-9 to be the default gcc:

sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-9 60 --slave /usr/bin/g++ g++ /usr/bin/g++-9
sudo update-alternatives --config gcc
# And make sure gcc-9 is the default

gym

git clone https://github.com/openai/gym-http-api
cd gym-http-api
pip install -r requirements.txt

Build

git clone https://github.com/Maverobot/deep_reinforcement_learning_in_action.git
cd deep_reinforcement_learning_in_action
mkdir build && cd build && cmake .. -DCMAKE_BUILD_TYPE=Release && cmake --build . -- -j4

Examples

Deep Q-learning for grid world

cd deep_reinforcement_learning_in_action
./dq_learning

Policy gradient for CartPole problem

Start gym

cd gym-http-api
python gym_http_server.py

Start policy gradient

cd deep_reinforcement_learning_in_action
./policy_gradient