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Develop package docs (#3551)
Develop package docs (#3551)
* Improvements to the main repo Readme: put an emphasis on the Releases section. * Improving the installation guide. * Added the first draft of package readme./bug-failed-api-check
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108README.md
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93com.unity.ml-agents/Documentation~/index.md
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160docs/Installation.md
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35docs/Limitations.md
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3com.unity.ml-agents/Documentation~/TableOfContents.md
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5com.unity.ml-agents/README.md
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Please see the [ML-Agents README)(https://github.com/Unity-Technologies/ml-agents/blob/master/README.md) |
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# About ML-Agents package (`com.unity.ml-agents`) |
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The Unity ML-Agents package contains the C# SDK for the |
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[Unity ML-Agents Toolkit](https://github.com/Unity-Technologies/ml-agents). |
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The package provides the ability for any Unity scene to be converted into a learning |
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environment where character behaviors can be trained using a variety of machine learning |
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algorithms. Additionally, it enables any trained behavior to be embedded back into the Unity |
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scene. More specifically, the package provides the following core functionalities: |
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* Define Agents: entities whose behavior will be learned. Agents are entities |
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that generate observations (through sensors), take actions and receive rewards from |
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the environment. |
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* Define Behaviors: entities that specifiy how an agent should act. Multiple agents can |
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share the same Behavior and a scene may have multiple Behaviors. |
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* Record demonstrations of an agent within the Editor. These demonstrations can be |
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valuable to train a behavior for that agent. |
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* Embedding a trained behavior into the scene via the |
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[Unity Inference Engine](https://docs.unity3d.com/Packages/com.unity.barracuda@latest/index.html). |
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Thus an Agent can switch from a learning behavior to an inference behavior. |
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Note that this package does not contain the machine learning algorithms for training |
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behaviors. It relies on a Python package to orchestrate the training. This package |
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only enables instrumenting a Unity scene and setting it up for training, and then |
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embedding the trained model back into your Unity scene. |
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## Preview package |
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This package is available as a preview, so it is not ready for production use. |
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The features and documentation in this package might change before it is verified for release. |
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## Package contents |
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The following table describes the package folder structure: |
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|**Location**|**Description**| |
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|---|---| |
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|*Documentation~*|Contains the documentation for the Unity package.| |
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|*Editor*|Contains utilities for Editor windows and drawers.| |
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|*Plugins*|Contains third-party DLLs.| |
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|*Runtime*|Contains core C# APIs for integrating ML-Agents into your Unity scene. | |
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|*Tests*|Contains the unit tests for the package.| |
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<a name="Installation"></a> |
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## Installation |
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To install this package, follow the instructions in the |
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[Package Manager documentation](https://docs.unity3d.com/Manual/upm-ui-install.html). |
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To install the Python package to enable training behaviors, follow the instructions on our |
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[GitHub repository](https://github.com/Unity-Technologies/ml-agents/blob/latest_release/docs/Installation.md). |
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## Requirements |
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This version of the Unity ML-Agents package is compatible with the following versions of the Unity Editor: |
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* 2018.4 and later (recommended) |
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## Known limitations |
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### Headless Mode |
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If you enable Headless mode, you will not be able to collect visual observations |
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from your agents. |
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### Rendering Speed and Synchronization |
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Currently the speed of the game physics can only be increased to 100x real-time. |
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The Academy also moves in time with FixedUpdate() rather than Update(), so game |
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behavior implemented in Update() may be out of sync with the agent decision |
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making. See |
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[Execution Order of Event Functions](https://docs.unity3d.com/Manual/ExecutionOrder.html) |
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for more information. |
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You can control the frequency of Academy stepping by calling |
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`Academy.Instance.DisableAutomaticStepping()`, and then calling |
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`Academy.Instance.EnvironmentStep()` |
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### Unity Inference Engine Models |
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Currently, only models created with our trainers are supported for running |
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ML-Agents with a neural network behavior. |
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## Helpful links |
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If you are new to the Unity ML-Agents package, or have a question after reading |
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the documentation, you can checkout our |
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[GitHUb Repository](https://github.com/Unity-Technologies/ml-agents), which |
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also includes a number of ways to |
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[connect with us](https://github.com/Unity-Technologies/ml-agents#community-and-feedback) |
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including our [ML-Agents Forum](https://forum.unity.com/forums/ml-agents.453/). |
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# Limitations |
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## Unity SDK |
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### Headless Mode |
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If you enable Headless mode, you will not be able to collect visual observations |
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from your agents. |
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### Rendering Speed and Synchronization |
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|
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Currently the speed of the game physics can only be increased to 100x real-time. |
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The Academy also moves in time with FixedUpdate() rather than Update(), so game |
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behavior implemented in Update() may be out of sync with the agent decision |
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making. See |
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[Execution Order of Event Functions](https://docs.unity3d.com/Manual/ExecutionOrder.html) |
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for more information. |
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|
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You can control the frequency of Academy stepping by calling |
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`Academy.Instance.DisableAutomaticStepping()`, and then calling |
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`Academy.Instance.EnvironmentStep()` |
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### Unity Inference Engine Models |
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Currently, only models created with our trainers are supported for running |
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ML-Agents with a neural network behavior. |
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## Python API |
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### Python version |
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As of version 0.3, we no longer support Python 2. |
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See the package-specific Limitations pages: |
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* [Unity `com.unity.mlagents` package](../com.unity.ml-agents/Documentation~/index.md) |
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* [`mlagents` Python package](../ml-agents/README.md) |
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* [`mlagents_envs` Python package](../ml-agents-envs/README.md) |
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* [`gym_unity` Python package](../gym-unity/README.md) |
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| 宽度: 1002 | 高度: 1150 | 大小: 266 KiB |
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* [ML-Agents README](https://github.com/Unity-Technologies/ml-agents/blob/master/README.md) |
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* [Contributing](../CONTRIBUTING.md) |
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* [Code of Conduct](https://github.com/Unity-Technologies/ml-agents/blob/master/CODE_OF_CONDUCT.md) |
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# Unity ML-Agents SDK |
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Contains the ML-Agents Unity Project, including |
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both the core plugin (in `Scripts`), as well as a set |
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of example environments (in `Examples`). |
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