https://github.com/stable-baselines-team/stable-baselines3-contrib
Contrib package for Stable-Baselines3 - Experimental reinforcement learning (RL) code
https://github.com/stable-baselines-team/stable-baselines3-contrib
experimental gsde gym machine-learning openai pytorch reinforcement-learning reinforcement-learning-algorithms research rl robotics sde stable-baselines
Last synced: about 2 months ago
JSON representation
Contrib package for Stable-Baselines3 - Experimental reinforcement learning (RL) code
- Host: GitHub
- URL: https://github.com/stable-baselines-team/stable-baselines3-contrib
- Owner: Stable-Baselines-Team
- License: mit
- Created: 2020-09-20T20:09:56.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2025-03-31T15:42:21.000Z (3 months ago)
- Last Synced: 2025-05-13T09:07:26.849Z (about 2 months ago)
- Topics: experimental, gsde, gym, machine-learning, openai, pytorch, reinforcement-learning, reinforcement-learning-algorithms, research, rl, robotics, sde, stable-baselines
- Language: Python
- Homepage: https://sb3-contrib.readthedocs.io
- Size: 1.43 MB
- Stars: 589
- Watchers: 17
- Forks: 194
- Open Issues: 79
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Citation: CITATION.bib
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- awesome-ChatGPT-repositories - stable-baselines3-contrib - Contrib package for Stable-Baselines3 - Experimental reinforcement learning (RL) code (Openai)
README
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# Stable-Baselines3 - Contrib (SB3-Contrib)
Contrib package for [Stable-Baselines3](https://github.com/DLR-RM/stable-baselines3) - Experimental reinforcement learning (RL) code.
"sb3-contrib" for short.
### What is SB3-Contrib?
A place for RL 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 the existing code without creating 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 us to provide reliable implementations following stable-baselines usual standards (consistent style, documentation, etc) beyond the relatively small scope of utilities in the main repository.
## Features
See documentation for the full list of included features.
**RL Algorithms**:
- [Augmented Random Search (ARS)](https://arxiv.org/abs/1803.07055)
- [Quantile Regression DQN (QR-DQN)](https://arxiv.org/abs/1710.10044)
- [PPO with invalid action masking (MaskablePPO)](https://arxiv.org/abs/2006.14171)
- [PPO with recurrent policy (RecurrentPPO aka PPO LSTM)](https://ppo-details.cleanrl.dev//2021/11/05/ppo-implementation-details/)
- [Truncated Quantile Critics (TQC)](https://arxiv.org/abs/2005.04269)
- [Trust Region Policy Optimization (TRPO)](https://arxiv.org/abs/1502.05477)
- [Batch Normalization in Deep Reinforcement Learning (CrossQ)](https://openreview.net/forum?id=PczQtTsTIX)
**Gym Wrappers**:
- [Time Feature Wrapper](https://arxiv.org/abs/1712.00378)
## Documentation
Documentation is available online: [https://sb3-contrib.readthedocs.io/](https://sb3-contrib.readthedocs.io/)
## Installation
To install Stable Baselines3 contrib with pip, execute:
```
pip install sb3-contrib
```
We recommend to use the `master` version of [Stable Baselines3](https://github.com/DLR-RM/stable-baselines3/).
To install Stable Baselines3 `master` version:
```
pip install git+https://github.com/DLR-RM/stable-baselines3
```
To install Stable Baselines3 contrib `master` version:
```
pip install git+https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
```
## How To Contribute
If you want to contribute, please read [**CONTRIBUTING.md**](./CONTRIBUTING.md) guide first.
## Citing the Project
To cite this repository in publications (please cite SB3 directly):
```bibtex
@article{stable-baselines3,
author = {Antonin Raffin and Ashley Hill and Adam Gleave and Anssi Kanervisto and Maximilian Ernestus and Noah Dormann},
title = {Stable-Baselines3: Reliable Reinforcement Learning Implementations},
journal = {Journal of Machine Learning Research},
year = {2021},
volume = {22},
number = {268},
pages = {1-8},
url = {http://jmlr.org/papers/v22/20-1364.html}
}
```