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Changed to material mkdocs theme. Minor doc updates. (#5835)
* Changed to material mkdocs theme. Minor doc updates. * Updated colors and home banner.
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docs/Installation.md

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@@ -18,7 +18,7 @@ The ML-Agents Toolkit contains several components:
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a Unity scene. It is a foundational layer that facilitates data messaging
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between Unity scene and the Python machine learning algorithms.
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Consequently, `mlagents` depends on `mlagents_envs`.
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- Unity [Project](../Project/) that contains several
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- Unity [Project](https://github.com/Unity-Technologies/ml-agents/tree/main/Project/) that contains several
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[example environments](Learning-Environment-Examples.md) that highlight the
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various features of the toolkit to help you get started.
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1. Select the `package.json` file.
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<p align="center">
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<img src="images/unity_package_manager_window.png"
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<img src="../images/unity_package_manager_window.png"
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alt="Unity Package Manager Window"
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height="300"
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height="150"
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border="10" />
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<img src="images/unity_package_json.png"
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<img src="../images/unity_package_json.png"
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alt="package.json"
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height="300"
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height="150"
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</p>
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docs/Learning-Environment-Examples.md

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# Example Learning Environments
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<img src="images/example-envs.png" align="middle" width="3000"/>
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<img src="../images/example-envs.png" align="middle" width="3000"/>
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The Unity ML-Agents Toolkit includes an expanding set of example environments
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that highlight the various features of the toolkit. These environments can also

docs/Limitations.md

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See the package-specific Limitations pages:
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- [`com.unity.mlagents` Unity package](https://docs.unity3d.com/Packages/com.unity.ml-agents@2.1/manual/index.html#known-limitations)
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- [`mlagents` Python package](ML-Agents-README.md)
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- [`mlagents_envs` Python package](../ml-agents-envs/README.md#limitations)
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- [`com.unity.mlagents` Unity package](https://docs.unity3d.com/Packages/com.unity.ml-agents@2.3/manual/index.html#known-limitations)
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- [`mlagents` Python package](../ml-agents/)
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- [`mlagents_envs` Python package](../ml-agents-envs/)

docs/Readme.md

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- Support for training single-agent, multi-agent cooperative, and multi-agent
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competitive scenarios via several Deep Reinforcement Learning algorithms (PPO, SAC, MA-POCA, self-play).
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- Support for learning from demonstrations through two Imitation Learning algorithms (BC and GAIL).
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- Quickly and easily add your own [custom training algorithm](Python-Custom-Trainer-Plugin.md) and/or components.
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- Easily definable Curriculum Learning scenarios for complex tasks
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- Train robust agents using environment randomization
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- Flexible agent control with On Demand Decision Making
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- Wrap Unity learning environments as a [PettingZoo](Python-PettingZoo-API.md) environment
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See our [ML-Agents Overview](ML-Agents-Overview.md) page for detailed
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descriptions of all these features.
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descriptions of all these features. Or go straight to our [web docs](https://unity-technologies.github.io/ml-agents/).
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## Releases & Documentation
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**Our latest, stable release is `Release 20`. Click
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[here](https://github.com/Unity-Technologies/ml-agents/tree/release_20_docs/docs/Readme.md)
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[here](Getting-Started.md)
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to get started with the latest release of ML-Agents.**
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**You can also check out our new [web docs](https://unity-technologies.github.io/ml-agents/)!**
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The table below lists all our releases, including our `main` branch which is
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under active development and may be unstable. A few helpful guidelines:
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- The [Versioning page](Versioning.md) overviews how we manage our GitHub
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### More from Unity
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- [Unity Simulation Pro](https://unity.com/products/unity-simulation-pro)
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- [Unity Robotics](https://github.com/Unity-Technologies/Unity-Robotics-Hub)
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- [Unity Computer Vision](https://unity.com/computer-vision)
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- [Unity Computer Vision](https://github.com/Unity-Technologies/com.unity.perception)
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## Community and Feedback
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{!../com.unity.ml-agents.extensions/Documentation~/com.unity.ml-agents.extensions.md!}

docs/extra.css

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.md-typeset__scrollwrap {
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margin: 1em -.8rem;
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docs/index.md

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<img src="images/U_MachineLearningAgents_Logo_Black_RGB.png" align="middle" width="3000"/>
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{!README.md!}

docs/ml-agents-envs.md

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{!../ml-agents-envs/README.md!}

docs/ml-agents.md

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{!../ml-agents/README.md!}

mkdocs.yml

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edit_uri: edit/main/docs/
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site_description: The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents.
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site_author: Unity Technologies
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copyright: com.unity.ml-agents copyright © 2017 Unity Technologies
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pages:
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copyright: com.unity.ml-agents copyright © 2017 - 2022 Unity Technologies
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nav:
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- Home: index.md
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- ML-Agents Overview: ML-Agents-Overview.md
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- Toolkit Documentation: ML-Agents-Toolkit-Documentation.md
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- Gym API Documentation: Python-Gym-API-Documentation.md
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- Petting Zoo Documentation: Python-PettingZoo-API-Documentation.md
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- LLAPI Documentation: Python-LLAPI-Documentation.md
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- On/Off Policy Trainer: Python-On-Off-Policy-Trainer-Documentation.md
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- Tutorials:
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- Custom Trainer Plugin: Tutorial-Custom-Trainer-Plugin.md
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- About:
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- FAQs: FAQ.md
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- Limitations: Limitations.md
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- Migrating: Migrating.md
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- Versioning: Versioning.md
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theme: readthedocs
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extra_css: [extra.css]
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theme:
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name: material
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logo: images/unity-logo.png
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favicon: images/unity-logo-black.png
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accent: light blue
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extra_css:
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base_path: docs

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