aravindr93 / Mjrl
Licence: apache-2.0
Reinforcement learning algorithms for MuJoCo tasks
Stars: ✭ 162
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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.
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].