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* updating the documentation website * adding the built docs * update of api docstrings across coach and tutorials 0-2 * added some missing api documentation * New Sphinx based documentation
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1.6 KiB
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32 lines
1.6 KiB
ReStructuredText
Environments
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============
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Coach supports a large number of environments which can be solved using reinforcement learning.
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To find a detailed documentation of the environments API, see the `environments section <../components/environments/index.html>`_.
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The supported environments are:
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* `DeepMind Control Suite <https://github.com/deepmind/dm_control>`_ - a set of reinforcement learning environments
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powered by the MuJoCo physics engine.
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* `Blizzard Starcraft II <https://github.com/deepmind/pysc2>`_ - a popular strategy game which was wrapped with a
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python interface by DeepMind.
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* `ViZDoom <http://vizdoom.cs.put.edu.pl/>`_ - a Doom-based AI research platform for reinforcement learning
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from raw visual information.
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* `CARLA <https://github.com/carla-simulator/carla>`_ - an open-source simulator for autonomous driving research.
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* `OpenAI Gym <https://gym.openai.com/>`_ - a library which consists of a set of environments, from games to robotics.
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Additionally, it can be extended using the API defined by the authors.
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In Coach, we support all the native environments in Gym, along with several extensions such as:
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* `Roboschool <https://github.com/openai/roboschool>`_ - a set of environments powered by the PyBullet engine,
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that offer a free alternative to MuJoCo.
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* `Gym Extensions <https://github.com/Breakend/gym-extensions>`_ - a set of environments that extends Gym for
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auxiliary tasks (multitask learning, transfer learning, inverse reinforcement learning, etc.)
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* `PyBullet <https://github.com/bulletphysics/bullet3/tree/master/examples/pybullet>`_ - a physics engine that
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includes a set of robotics environments.
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