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

cargo run --release --example chain-tabular-q

This environment has infinitely long episodes.

Cart-Pole with Trust-Region Policy Optimization

cargo run --release --example cartpole-trpo

cargo run --release --example cartpole-trpo data/cartpole-trpo/<time>/actor.cbor

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.