offlinerllib 0.0.4

A python module desgined for Offline RL algorithms developing and benchmarking.

OfflineRL-Lib

🚧 This repo is not ready for release, benchmarking is ongoing. 🚧

OfflineRL-Lib provides unofficial and benchmarked PyTorch implementations for selected OfflineRL algorithms, including:

• In-Sample Actor Critic (InAC)
• Extreme Q-Learning (XQL)
• Implicit Q-Learning (IQL)
• Decision Transformer (DT)
• Advantage-Weighted Actor Critic (AWAC)
• TD3-BC

still benchmarking ...

• EDAC
• SAC-N

under developing (model based algorithms) ...

• MOPO
• MAPLE
• RAMBO

Benchmark Results

See reproduce/benchmark_result.md for details.

Citing OfflineRL-Lib

If you use OfflineRL-Lib in your work, please use the following bibtex

@misc{offinerllib,
  author = {Chenxiao Gao},
  title = {OfflineRL-Lib: Benchmarked Implementations of Offline RL Algorithms},
  year = {2023},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/typoverflow/OfflineRL-Lib}},
}

Acknowledgements

We thank CORL for providing finetuned hyper-parameters.