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docs_raw/docs/design/features.md

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