RL for MuJoCo
This package contains implementations of various RL algorithms for continuous control tasks simulated with MuJoCo.
Installation
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.
Bibliography
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},
}
Credits
This package is maintained by Aravind Rajeswaran and other members of the Movement Control Lab, University of Washington Seattle.