How to Contribute to ML-Agents

1.Fork the repository

Fork the ML-Agents repository by clicking on the "Fork" button in the top right corner of the GitHub page. This creates a copy of the repository under your GitHub account.

2. Set up your development environment

Clone the forked repository to your local machine using Git. Install the necessary dependencies and follow the instructions provided in the project's documentation to set up your development environment properly.

3. Choose an issue or feature

Browse the project's issue tracker or discussions to find an open issue or feature that you would like to contribute to. Read the guidelines and comments associated with the issue to understand the requirements and constraints.

4. Make your changes

Create a new branch for your changes based on the main branch of the ML-Agents repository. Implement your code changes or add new features as necessary. Ensure that your code follows the project's coding style and conventions.

Example: Let's say you want to add support for a new type of reward function in the ML-Agents framework. You can create a new branch named feature/reward-function to implement this feature.

5. Test your changes

Run the appropriate tests to ensure your changes work as intended. If necessary, add new tests to cover your code and verify that it doesn't introduce regressions.

Example: For the reward function feature, you would write tests to check different scenarios and expected outcomes of the new reward function.

6. Submit a pull request

Push your branch to your forked repository and submit a pull request (PR) to the ML-Agents main repository. Provide a clear and concise description of your changes, explaining the problem you solved or the feature you added.

Example: In the pull request description, you would explain how the new reward function works, its benefits, and any relevant implementation details.

7. Respond to feedback

Be responsive to any feedback or comments provided by the project maintainers. Address the feedback by making necessary revisions to your code and continue the discussion if required.

8. Continuous integration and code review

The ML-Agents project utilizes automated continuous integration (CI) systems to run tests on pull requests. Address any issues flagged by the CI system and actively participate in the code review process by addressing comments from reviewers.

9. Merge your changes

Once your pull request has been approved and meets all the project's requirements, a project maintainer will merge your changes into the main repository. Congratulations, your contribution has been successfully integrated!

Remember to always adhere to the project's code of conduct, be respectful, and follow any specific contribution guidelines provided by the ML-Agents project. Happy contributing!

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