Welcome to garage¶
garage is a framework for developing and evaluating reinforcement learning algorithms.
garage is a work in progress, input is welcome. The available documentation is limited for now.
The garage user guide explains how to install garage, how to run experiments, and how to implement new MDPs and new algorithms.
- Running Experiments
- Implementing New Environments
- Implementing New Algorithms (Basic)
- Implementing New Algorithms (Advanced)
If you use garage for academic research, you are highly encouraged to cite the following paper:
- Yan Duan, Xi Chen, Rein Houthooft, John Schulman, Pieter Abbeel. “Benchmarking Deep Reinforcement Learning for Continuous Control. Proceedings of the 33rd International Conference on Machine Learning (ICML), 2016.