garage is a toolkit for developing and evaluating reinforcement learning algorithms, and an accompanying library of state-of-the-art implementations built using that toolkit.

garage is a work in progress, input is welcome. The available documentation is limited, but rapidly growing.

User Guide

The garage user guide explains how to install garage, how to run experiments, and how to implement new MDPs and new algorithms.

Citing garage

If you use garage for academic research, please cite the repository using the following BibTeX entry. You should update the commit field with the commit or release tag your publication uses.

  author = {The garage contributors},
  title = {Garage: A toolkit for reproducible reinforcement learning research},
  year = {2019},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{}},
  commit = {ebd7800430b0212c3ffcf78fd3ec26b22097c371}

Indices and tables