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<h1 id="coach-features">Coach Features</h1>
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<h2 id="supported-algorithms">Supported Algorithms</h2>
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<p>Coach supports many state-of-the-art reinforcement learning algorithms, which are separated into two main classes -
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value optimization and policy optimization. A detailed description of those algorithms may be found in the algorithms
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section.</p>
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<p style="text-align: center;">
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<img src="../../img/algorithms.png" alt="Supported Algorithms" style="width: 600px;"/>
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</p>
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<h2 id="supported-environments">Supported Environments</h2>
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<p>Coach supports a large number of environments which can be solved using reinforcement learning:</p>
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<ul>
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<li>
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<p><strong><a href="https://github.com/deepmind/dm_control">DeepMind Control Suite</a></strong> - a set of reinforcement learning environments
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powered by the MuJoCo physics engine.</p>
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</li>
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<li>
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<p><strong><a href="https://github.com/deepmind/pysc2">Blizzard Starcraft II</a></strong> - a popular strategy game which was wrapped with a
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python interface by DeepMind.</p>
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</li>
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<li>
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<p><strong><a href="http://vizdoom.cs.put.edu.pl/">ViZDoom</a></strong> - a Doom-based AI research platform for reinforcement learning
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from raw visual information.</p>
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</li>
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<li>
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<p><strong><a href="https://github.com/carla-simulator/carla">CARLA</a></strong> - an open-source simulator for autonomous driving research.</p>
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</li>
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<li>
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<p><strong><a href="https://gym.openai.com/">OpenAI Gym</a></strong> - 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.</p>
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</li>
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</ul>
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<p>In Coach, we support all the native environments in Gym, along with several extensions such as:</p>
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<ul>
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<li>
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<p><strong><a href="https://github.com/openai/roboschool">Roboschool</a></strong> - a set of environments powered by the PyBullet engine,
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that offer a free alternative to MuJoCo.</p>
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</li>
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<li>
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<p><strong><a href="https://github.com/Breakend/gym-extensions">Gym Extensions</a></strong> - a set of environments that extends Gym for
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auxiliary tasks (multitask learning, transfer learning, inverse reinforcement learning, etc.)</p>
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</li>
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<li>
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<p><strong><a href="https://github.com/bulletphysics/bullet3/tree/master/examples/pybullet">PyBullet</a></strong> - a physics engine that
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includes a set of robotics environments.</p>
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</li>
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