CORL: Offline Reinforcement Learning Library

Offline RL is a fresh paradigm that makes RL similar to the supervised learning, thus making it better applicable to the real-world problems. There is a whole bunch of recently developed Offline RL aglorithms, however, there was nots many of reliable open-sourced implementations for such algorithms

Our friends from @tinkoffai do some research in this direction and they recently open-sourced their internal offline RL library.

The main features are:
- Single-file implementations
- SOTA algorithms (Decision Transformer, AWAC, BC, CQL, IQL, TD3+BC, SAC-N, EDAC)
- Benchmarked on widely used D4RL datasets (results match performances reported in the original papers)
- Wandb logs for all of the experiments

Hope you will like it and the whole new world of Offline RL!

Github: https://github.com/tinkoff-ai/CORL

#tinkoff #RL #offline_lib