Training Unity Machine Learning Agents using reinforcement learning method

This study aims to provide research of Machine Learning tools combined with Unity platform, to develop several Machine Learning Agents in various environments using multiple environment configurations and training scenarios. This work introduces a single competitive agent environment where the agent compete with simulated physics in a 3D world. Although the rules of the environment are generally basic, the trained agent learns a wide variety of interesting and complex solutions.