Reinforcement learning algorithms for MuJoCo tasks
This package contains implementations of various RL algorithms for continuous control tasks simulated with MuJoCo.
The main package dependencies are
MuJoCo,
python=3.7,
gym>=0.13,
mujoco-py>=2.0, and
pytorch>=1.0. See
setup/README.md(link) for detailed install instructions.
If you find the package useful, please cite the following papers. ``` @INPROCEEDINGS{Rajeswaran-NIPS-17, AUTHOR = {Aravind Rajeswaran and Kendall Lowrey and Emanuel Todorov and Sham Kakade}, TITLE = "{Towards Generalization and Simplicity in Continuous Control}", BOOKTITLE = {NIPS}, YEAR = {2017}, }
@INPROCEEDINGS{Rajeswaran-RSS-18, AUTHOR = {Aravind Rajeswaran AND Vikash Kumar AND Abhishek Gupta AND Giulia Vezzani AND John Schulman AND Emanuel Todorov AND Sergey Levine}, TITLE = "{Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations}", BOOKTITLE = {Proceedings of Robotics: Science and Systems (RSS)}, YEAR = {2018}, } ```
This package is maintained by Aravind Rajeswaran and other members of the Movement Control Lab, University of Washington Seattle.