sbx-rl


Namesbx-rl JSON
Version 0.20.0 PyPI version JSON
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home_pagehttps://github.com/araffin/sbx
SummaryJax version of Stable Baselines, implementations of reinforcement learning algorithms.
upload_time2025-02-14 11:03:47
maintainerNone
docs_urlNone
authorAntonin Raffin
requires_python>=3.9
licenseMIT
keywords reinforcement-learning-algorithms reinforcement-learning machine-learning gym gymnasium jax openai stable baselines toolbox python data-science
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            

# Stable Baselines Jax (SB3 + JAX = SBX)

See https://github.com/araffin/sbx

Proof of concept version of [Stable-Baselines3](https://github.com/DLR-RM/stable-baselines3) in Jax.

Implemented algorithms:
- [Soft Actor-Critic (SAC)](https://arxiv.org/abs/1801.01290) and [SAC-N](https://arxiv.org/abs/2110.01548)
- [Truncated Quantile Critics (TQC)](https://arxiv.org/abs/2005.04269)
- [Dropout Q-Functions for Doubly Efficient Reinforcement Learning (DroQ)](https://openreview.net/forum?id=xCVJMsPv3RT)
- [Proximal Policy Optimization (PPO)](https://arxiv.org/abs/1707.06347)
- [Deep Q Network (DQN)](https://arxiv.org/abs/1312.5602)
- [Twin Delayed DDPG (TD3)](https://arxiv.org/abs/1802.09477)
- [Deep Deterministic Policy Gradient (DDPG)](https://arxiv.org/abs/1509.02971)
- [Batch Normalization in Deep Reinforcement Learning (CrossQ)](https://openreview.net/forum?id=PczQtTsTIX)
- [Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning (SimBa)](https://openreview.net/forum?id=jXLiDKsuDo)

## Example

```python
from sbx import DDPG, DQN, PPO, SAC, TD3, TQC, CrossQ

model = TQC("MlpPolicy", "Pendulum-v1", verbose=1)
model.learn(total_timesteps=10_000, progress_bar=True)


            

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