Unity ML-Agents Project for Agent Control

Project Description

• The purpose of this project is to train and evaluate autonomous agents in the Unity game engine using the ML-Agents toolkit. By applying Deep Reinforcement Learning (DRL) algorithms, we aim to teach these agents to make decisions and perform tasks effectively in a 3D environment. Specifically, the project involves setting up training environments, adjusting learning parameters, and implementing custom sensor inputs to optimize the agents' performance. The overall goal is to analyze how well different DRL algorithms and environmental setups contribute to agent learning and behavior in complex, dynamic scenarios.

Objectives

• Set up the necessary tools: Install and configure Unity, the ML-Agents toolkit, and Git for version control to ensure a smooth development process.
• Create a project plan: Develop a detailed plan for the entire semester, outlining key milestones, tasks, and timelines to guide the project's progress.
• Familiarize the team with tools: Ensure that all team members understand how to use Unity, ML-Agents, and Git, covering both basic and advanced functionalities.
• Make small code modifications: Implement minor changes to the ML-Agents environment to gain a hands-on understanding of how agents, algorithms, and environments interact. This experimentation will lay the groundwork for more complex tasks in later phases.

Installation and How to Run

1. Unity: Download Unity
2. Python and Virtual Environment: Follow the steps to set up Python and create a virtual environment for ML-Agents.
3. Git-Hub Repository Cloning: Clone the repository from recommended branch.
4. Unity Setup With The Git Open the project file in Unity which is located in Main\ml-agents\Project of the git repository.
5. Follow the Unity Setup Process This will conclude the setup.

Team Members

• Team Members Name - (Their Github Nickname)

1. Julia - (julca2706)
   • Addition of particles for Worm Agent
   • Extraction of general tasks, Gantt Chart
2. Kennedy - (Kennedy531)
   • Changed team colors for football agent
   • Phase 1 Overview
3. Mika - (mikahagenbeek692)
   • Increase Sorter Agent speed
   • Phase 3 Detailed Planning
4. Mila - (MilaSpasova)
   • Adding color-changing logic to Crawler Agent
   • Phase 2 Detailed Planning
5. Levent - (Itzy-B)
   • README file, In Wall Jump Agent, changed, speed of movement, wall height range, jumping time, the obstacle height, the field size
   • Introduction, Risk Analysis
6. Florien - (front-depiction)
   • Implement dynamic movement sensitivity for Ball3D Agent
   • Conclusion
7. Srijith - (Glitch719)
   • Altering walker movement speed
   • Block Diagram

Current Status

• The current state of the project is that there have been small changes made to multiple agents. It runs perfectly as required and all tools are installed.

Contribution Guidelines

We welcome contributions to this project! Please follow these steps to contribute:

Creating Branches

• Clone the repository:
  • git clone https://github.com/AIML21/main.git
  • cd main
• Before creating a new branch, ensure your local repository is up to date:
  • git pull origin main
• Create a new branch for your work:
  • git checkout -b

Note: Use clear, descriptive names for branches, such as feature-add-custom-sensor or bugfix-training-algorithm.

Making Commits

• After making changes, add the files you want to commit:
  • git add or git add.
• Commit your changes with a meaningful message:
  • git commit -m "Describe your changes"

Submitting Pull Requests

• Push your branch to the remote repository:
  • git push origin

License

MIT License

Copyright (c) 2024 [Unity ML-Agents Project for Agent Control]

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Acknowledgments

We would like to thank the following resources and individuals for their support: - Unity ML-Agents Toolkit: ML-Agents GitHub Repository - Documentation: Unity and ML-Agents official documentation Unity Documentation and ML-Agents Toolkit Documentation - Special thanks to every team member and [miguelalonsojr] for their contributions to the project.