Welcome to Stable Baselines docs! - RL Baselines Made Easy

Stable Baselines is a set of improved implementations of Reinforcement Learning (RL) algorithms based on OpenAI Baselines.

Github repository: https://github.com/hill-a/stable-baselines

RL Baselines Zoo (collection of pre-trained agents): https://github.com/araffin/rl-baselines-zoo

RL Baselines zoo also offers a simple interface to train, evaluate agents and do hyperparameter tuning.

You can read a detailed presentation of Stable Baselines in the Medium article: link

Note

Stable-Baselines3 (PyTorch edition) beta is now online: https://github.com/DLR-RM/stable-baselines3

Main differences with OpenAI Baselines

This toolset is a fork of OpenAI Baselines, with a major structural refactoring, and code cleanups:

  • Unified structure for all algorithms
  • PEP8 compliant (unified code style)
  • Documented functions and classes
  • More tests & more code coverage
  • Additional algorithms: SAC and TD3 (+ HER support for DQN, DDPG, SAC and TD3)

User Guide

Citing Stable Baselines

To cite this project in publications:

@misc{stable-baselines,
  author = {Hill, Ashley and Raffin, Antonin and Ernestus, Maximilian and Gleave, Adam and Kanervisto, Anssi and Traore, Rene and Dhariwal, Prafulla and Hesse, Christopher and Klimov, Oleg and Nichol, Alex and Plappert, Matthias and Radford, Alec and Schulman, John and Sidor, Szymon and Wu, Yuhuai},
  title = {Stable Baselines},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/hill-a/stable-baselines}},
}

Contributing

To any interested in making the rl baselines better, there is still some improvements that needs to be done. A full TODO list is available in the roadmap.

If you want to contribute, please read CONTRIBUTING.md first.

Indices and tables