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google-deepmind/dm_control
Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
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29 Dec 2017
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README
the first lines# `dm_control`: Google DeepMind Infrastructure for Physics-Based Simulation.
Google DeepMind's software stack for physics-based simulation and Reinforcement
Learning environments, using MuJoCo physics.
An introductory tutorial for this package is available as a Colaboratory
notebook:
[](https://colab.research.google.com/github/google-deepmind/dm_control/blob/main/tutorial.ipynb)
## Overview
This package consists of the following "core" components:
- [`dm_control.mujoco`]: Libraries that provide Python bindings to the MuJoCo
physics engine.
- [`dm_control.suite`]: A set of Python Reinforcement Learning environments
powered by the MuJoCo physics engine.
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Recent commits
default branch- 1hAdd `castshadow` attribute to `<geom>` for per-geom shadow control. . Yuval Tassa
- 2hAdd an mjRND_POST_PROCESSING flag. . DeepMind
- 6dUpdate dm_control to version 1.0.50 and require MuJoCo 3.17.0 . DeepMind
- 9dSuppress new Pyrefly findings before upgrading to v1.4.0 . Oleh Prypin
- 10ddm_control: load exported MJCF relative to output dir in export_with_assets_test . Yuval Tassa
- 15dUpdate dm_control to version 1.0.49 and require MuJoCo 3.16.0 . DeepMind
- 23dUpdate dm_control to version 1.0.48 and require MuJoCo 3.15.0 . DeepMind
- 24dReplace `# pytype: disable` suppressions with `# pyrefly: ignore` . Oleh Prypin
- 36dUpdate dm_control to version 1.0.47 and require MuJoCo 3.14.0 . DeepMind
- 49dUpdate dm_control to version 1.0.46 and require MuJoCo 3.13.0 . DeepMind