Author(s)
Tassa, YuvalDoron, Yotam
Muldal, Alistair
Erez, Tom
Li, Yazhe
Casas, Diego de Las
Budden, David
Abdolmaleki, Abbas
Merel, Josh
Lefrancq, Andrew
Lillicrap, Timothy
Riedmiller, Martin
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http://arxiv.org/abs/1801.00690Abstract
The DeepMind Control Suite is a set of continuous control tasks with a standardised structure and interpretable rewards, intended to serve as performance benchmarks for reinforcement learning agents. The tasks are written in Python and powered by the MuJoCo physics engine, making them easy to use and modify. We include benchmarks for several learning algorithms. The Control Suite is publicly available at https://www.github.com/deepmind/dm_control . A video summary of all tasks is available at http://youtu.be/rAai4QzcYbs .Comment: 24 pages, 7 figures, 2 tables
Date
2018-01-02Type
textIdentifier
oai:arXiv.org:1801.00690http://arxiv.org/abs/1801.00690