ReLearn: A Reinforcement Learning Library
A reinforcement learning library and experiment runner. Uses pytorch as the neural network backend via the tch interface to the C++ API.
At the moment this is designed for personal use. It is in-development and unstable so expect breaking changes with updates.
Read the documentation at https://docs.rs/relearn.
Examples
Chain Environment with Tabular Q Learning
This environment has infinitely long episodes.
Cart-Pole with Trust-Region Policy Optimization
Uses a feed-forward MLP for the policy and a separate MLP for the critic
(baseline).
The displayed statistics are also saved to data/cartpole-trpo/
and can be
viewed with tensorboard --logdir data/cartpole-trpo
.