Stable Baselines3
Stable Baselines3 is a set of improved implementations of reinforcement learning algorithms in PyTorch. It is the next major version of Stable Baselines.
Github repository: https://github.com/DLR-RM/stable-baselines3
Documentation: https://stable-baselines3.readthedocs.io/
RL Baselines3 Zoo (collection of pre-trained agents): https://github.com/DLR-RM/rl-baselines3-zoo
RL Baselines3 Zoo also offers a simple interface to train, evaluate agents and do hyperparameter tuning.
Antonin Raffin
Research Engineer in Robotics and Machine Learning
Robots. Machine Learning. Blues Dance.
Posts
Stable-Baselines3: Reliable Reinforcement Learning Implementations
Publications
Stable-Baselines3: Reliable Reinforcement Learning Implementations
Stable-Baselines3 provides open-source implementations of deep reinforcement learning (RL) algorithms in Python. The implementations have been benchmarked against reference codebases, and automated unit tests cover 95% of the code. The algorithms follow a consistent interface and are accompanied by extensive documentation, making it simple to train and compare different RL algorithms. Our documentation, examples, and source-code are available at https://github.com/DLR-RM/stable-baselines3.
Smooth Exploration for Robotic Reinforcement Learning
We extend the original state-dependent exploration (SDE) to apply deep reinforcement learning algorithms directly on real robots. The resulting method, gSDE, yields competitive results in simulation but outperforms the unstructured exploration on the real robot.