3 releases (breaking)
0.3.0 | Jul 30, 2022 |
---|---|
0.2.0 | Mar 22, 2022 |
0.1.0 | Oct 7, 2021 |
#41 in #reinforcement-learning
61 downloads per month
Used in 2 crates
(via relearn)
30KB
586 lines
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
.
Dependencies
~1.5MB
~33K SLoC