A competitive 3D-Volleyball-Game using Reinforcement Learning with Unity ML-Agents


This project report describes the integration of reinforcement learning into a game development scenario by creating a competitive volleyball game using the Unity ML-Agents Toolkit. The work elaborates on what reinforcement learning is, brings forth some of the challenges of adding machine learning to a game, describes the development environment Unity and its machine learning package ML-Agents. Furthermore the implementation aspects are described including the environment setup, parameter tuning, reward engineering as well as the performance analysis of the trained agent.