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Stable-Baselines3 - Contrib
Contrib package for Stable-Baselines3 - Experimental code. "sb3-contrib" for short.
A place for training algorithms and tools that are considered experimental, e.g. implementations of the latest publications. Goal is to keep the simplicity, documentation and style of stable-baselines3 but for less matured implementations.
Why create this repository? Over the span of stable-baselines and stable-baselines3, the community has been eager to contribute in form of better logging utilities, environment wrappers, extended support (e.g. different action spaces) and learning algorithms. However sometimes these utilities were too niche to be considered for stable-baselines or proved to be too difficult to integrate well into existing code without a mess. sb3-contrib aims to fix this by not requiring the neatest code integration with existing code and not setting limits on what is too niche: almost everything remotely useful goes! We hope this allows to extend the known quality of stable-baselines style and documentation beyond the relatively small scope of utilities of the main repository.
Features
See documentation for the full list of included features.
Training algorithms:
Installation
Note: You need the master version of Stable Baselines3.
To install Stable Baselines3 master version:
pip install git+https://github.com/DLR-RM/stable-baselines3
Install Stable Baselines3 - Contrib using pip:
pip install git+https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
Citing the Project
To cite this repository in publications (please cite SB3 directly):
@misc{stable-baselines3,
author = {Raffin, Antonin and Hill, Ashley and Ernestus, Maximilian and Gleave, Adam and Kanervisto, Anssi and Dormann, Noah},
title = {Stable Baselines3},
year = {2019},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/DLR-RM/stable-baselines3}},
}