This project is used to implement all kinds of RL basic algorithms.
- algo to save the code regarding the algorithms' implementations
- docs to save the descriptions of the corresponding algorithms
- env to provide the env_wrapper (gym, gymnasium)
- model to save the network structure of policy, state-value function, action-value function
- util to save the code regrading the common tricks
- RainBow-DQN(initial, double, PER, dueling, multi-step, noisy)
- REINFORCE
- A2C (A2C Continuous / A2C Discrete)
- DDPG
- TD3
conda create --name basic_rl python=3.10
conda activate basic_rl
pip install torch torchvision
conda install swig
conda install gymnasium[all]
pip install tensorboardX tensorboard
apt-get install patchelf