Reinforcement Learning with RLlib in the Unity Game Engine

The Unity3D game engine can be used to train different agents using reinforcement learning (RL) techniques. The authors will use Ray RLlib, an open-source RL library, in conjunction with Unity's ML-Agents Toolkit to cover the heavy-lifting parts of training agents. They will start by training a single agent on a 3D ball game, where the goal is to balance balls without them falling down. After some time, the script will ask the user to press the "play" button again, and the agent will start acting and learning how to improve over time. The authors will then move on to a more complex scenario, such as a soccer game with two teams, where each team has to learn how to play against the other. To speed up the training process, they will use parallelization on their local machine by compiling the game into a headless executable and specifying the number of workers to use.

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