OfflineRL-Lib

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

For Model-Based algorithms, please check OfflineRL-Kit!

Benchmark Results

We benchmark and visualize the result via WandB. Click the following WandB links, and group the runs via the entry task (for offline experiments) or env (for online experiments).
Available Runs
- Offline:
  - TD7 📈
  - XQL 📈
  - InAC 📈
  - AWAC 📈
  - IQL 📈
  - TD3BC 📈
  - Decision Transformer 📈
- Online Runs
  - SAC 📈
  - TD3 📈
  - TD7 📈
  - XSAC 📈

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.

Metadata

Release files for offlinerllib 0.1.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for offlinerllib 0.1.5
File	Size	Uploaded
offlinerllib-0.1.5.tar.gz	38.5 kB	Dec 20, 2023	Details

Release files / offlinerllib-0.1.5.tar.gz

Download URL	offlinerllib-0.1.5.tar.gz
Size	38.5 kB
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SHA-256 checksum How to use checksums	`7f4e169c897764391adbcb21dec0d7b5d49d8a4540a5e932c0707c9b206d44c0`
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Upload date	Dec 20, 2023
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.2 CPython/3.11.7`