DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo. DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo physics. The MuJoCo Python bindings support three different OpenGL rendering backends: EGL (headless, hardware-accelerated), GLFW (windowed, hardware-accelerated), and OSMesa (purely software-based). At least one of these three backends must be available in order render through dm_control. Hardware rendering with a windowing system is supported via GLFW and GLEW. On Linux these can be installed using your distribution's package manager. "Headless" hardware rendering (i.e. without a windowing system such as X11) requires EXT_platform_device support in the EGL driver. While dm_control has been largely updated to use the pybind11-based bindings provided via the mujoco package, at this time it still relies on some legacy components that are automatically generated.

Features

  • Starting from version 1.0.0, we adopt semantic versioning
  • Install dm_control from PyPI
  • GLFW will not work on headless machines
  • The MuJoCo Python bindings support three different OpenGL rendering backends
  • Interactive environment viewer
  • Library for defining rich RL environments from reusable, self-contained components

Project Samples

Project Activity

See All Activity >

License

Apache License V2.0

Follow dm_control

dm_control Web Site

Other Useful Business Software
Earn up to 15% annual interest with Nexo. Icon
Earn up to 15% annual interest with Nexo.

Access competitive interest rates on your digital assets.

Generate interest, borrow against your crypto, and trade a range of cryptocurrencies — all in one platform. Geographic restrictions, eligibility, and terms apply.
Get started with Nexo.
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of dm_control!