Initial commit

Author: awjuliani

.gitignore

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+/unity-environment/[Ll]ibrary/
+/unity-environment/[Tt]emp/
+/unity-environment/[Oo]bj/
+/unity-environment/[Bb]uild/
+/unity-environment/[Bb]uilds/
+/unity-environment/Assets/AssetStoreTools*
+
+# Tensorflow Model Info
+/python/models
+/python/summaries
+
+# Visual Studio 2015 cache directory
+/unity-environment/.vs/
+
+# Autogenerated VS/MD/Consulo solution and project files
+/unity-environmentExportedObj/
+/unity-environment.consulo/
+*.csproj
+*.unityproj
+*.sln
+*.suo
+*.tmp
+*.user
+*.userprefs
+*.pidb
+*.booproj
+*.svd
+*.pdb
+
+# Unity3D generated meta files
+*.pidb.meta
+
+# Unity3D Generated File On Crash Reports
+/unity-environment/sysinfo.txt
+
+# Builds
+*.apk
+*.unitypackage
+*.app
+*.exe
+*.x86_64
+*.x86
+
+# Tensorflow Sharp Files
+/unity-environment/Assets/ML-Agents/Plugins/Android*
+/unity-environment/Assets/ML-Agents/Plugins/iOS*
+/unity-environment/Assets/ML-Agents/Plugins/Computer*
+/unity-environment/Assets/ML-Agents/Plugins/System*
+
+
+# Mac hidden files
+*.DS_Store
+*/.ipynb_checkpoints
+*/.idea
+*.pyc
+*.idea/misc.xml
+*.idea/modules.xml
+*.iml
+*.xml
+*.cache
+*/build/
+*/dist/
+*.egg-info*
+*.eggs*
+*.gitignore.swp
+
+.DS_Store

LICENSE

@@ -186,7 +186,7 @@
       same "printed page" as the copyright notice for easier
       identification within third-party archives.
 
-   Copyright {yyyy} {name of copyright owner}
+   Copyright 2017 Unity Technologies
 
    Licensed under the Apache License, Version 2.0 (the "License");
    you may not use this file except in compliance with the License.

README.md

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+![alt text](images/banner.png "Unity ML - Agents")
+
+
+# Unity ML - Agents
+**Unity Machine Learning Agents** allows researchers and developers to create games and simulations using the Unity Editor which serve as environments where intelligent agents can be trained using reinforcement learning, neuroevolution, or other machine learning methods through a simple-to-use Python API. For more information, see the [wiki page](../../wiki).
+
+For a walkthrough on how to train an agent in one of the provided example environments, start [here](../../wiki/Getting-Started-with-Balance-Ball).
+
+## Features
+* Unity Engine flexibility and simplicity
+* Multiple observations (cameras)
+* Flexible Multi-agent support
+* Discrete and continuous action spaces
+* Python (2 and 3) control interface
+* Visualizing network outputs in environment
+* Tensorflow Sharp Agent Embedding _[Experimental]_
+
+## Creating an Environment
+The _Agents SDK_, including example environment scenes is localted in `unity-environment` folder. For requirements, instructions, and other information, see the contained Readme and the relevant [wiki page](../../wiki/Making-a-new-Unity-Environment).
+
+## Training your Agents
+Once you've built a Unity Environment, example Reinforcement Learning algorithms and the Python API are available in the `python` folder. For requirements, instructions, and other information, see the contained Readme and the relevant [wiki page](../../wiki/Unity-Agents---Python-API).