Projects¶
This is a list of projects using stable-baselines3. Please tell us, if you want your project to appear on this page ;)
rl_reach¶
A platform for running reproducible reinforcement learning experiments for customisable robotic reaching tasks. This self-contained and straightforward toolbox allows its users to quickly investigate and identify optimal training configurations.
Generalized State Dependent Exploration for Deep Reinforcement Learning in Robotics¶
An exploration method to train RL agent directly on real robots. It was the starting point of Stable-Baselines3.
Reacher¶
A solution to the second project of the Udacity deep reinforcement learning course. It is an example of:
wrapping single and multi-agent Unity environments to make them usable in Stable-Baselines3
creating experimentation scripts which train and run A2C, PPO, TD3 and SAC models (a better choice for this one is https://github.com/DLR-RM/rl-baselines3-zoo)
generating several pre-trained models which solve the reacher environment
SUMO-RL¶
A simple interface to instantiate RL environments with SUMO for Traffic Signal Control.
Supports Multiagent RL
Compatibility with gym.Env and popular RL libraries such as stable-baselines3 and RLlib
Easy customisation: state and reward definitions are easily modifiable