Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目,它使游戏和模拟能够作为训练智能代理的环境。
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Contribution Guidelines

Thank you for your interest in contributing to the ML-Agents toolkit! We are incredibly excited to see how members of our community will use and extend the ML-Agents toolkit. To facilitate your contributions, we've outlined a brief set of guidelines to ensure that your extensions can be easily integrated.

Communication

First, please read through our code of conduct, as we expect all our contributors to follow it.

Second, before starting on a project that you intend to contribute to the ML-Agents toolkit (whether environments or modifications to the codebase), we strongly recommend posting on our Issues page and briefly outlining the changes you plan to make. This will enable us to provide some context that may be helpful for you. This could range from advice and feedback on how to optimally perform your changes or reasons for not doing it.

Lastly, if you're looking for input on what to contribute, feel free to reach out to us directly at ml-agents@unity3d.com and/or browse the GitHub issues with the contributions welcome label.

Git Branches

Starting with v0.3, we adopted the Gitflow Workflow. Consequently, the master branch corresponds to the latest release of the project, while the develop branch corresponds to the most recent, stable, version of the project.

Thus, when adding to the project, please branch off develop and make sure that your Pull Request (PR) contains the following:

  • Detailed description of the changes performed
  • Corresponding changes to documentation, unit tests and sample environments (if applicable)
  • Summary of the tests performed to validate your changes
  • Issue numbers that the PR resolves (if any)

Environments

We are also actively open to adding community contributed environments as examples, as long as they are small, simple, demonstrate a unique feature of the platform, and provide a unique non-trivial challenge to modern machine learning algorithms. Feel free to submit these environments with a PR explaining the nature of the environment and task.

Style Guide

When performing changes to the codebase, please ensure that all python code is reformatted using the black formatter. For C#, we will soon be requirements for style and formatting.