Design and Implement of Soccer Player AI Training System using Unity ML-Agents

Abstract:
Reinforcement learning is one of the paradigms and methodologies of machine learning, which is used to describe and solve problems in which agents learn strategies to maximize rewards or achieve specific goals in the process of interacting with the environment. However, the application of reinforcement learning to the real world has many limitations. Unity provides a special toolkit for simulating reinforcement learning, which can simulate the learning environment and train Agents in Unity. This article uses Unity to build an AI training environment for football players, and uses the Unity Machine Learning Agents toolkit for reinforcement learning. Through the design and implementation of such a system, a complete simulation reinforcement learning solution is provided for AI engineers.