After learning some Unity in my Virtual Reality class, I decided to test out the ML-Agents toolkit, an SDK of different machine learning algorithms for use in the Unity environment. I made a game of Pong and used reinforcement learning to train one paddle to hit the ball. I used multiple agents with multiple environements and randomized each episode to make the training faster and more accurate. The trained model ended up working pretty well with an average reward of 0.88 (1 being the best).
The left paddle is the trained agent moving on its own.
Made with <3 by Arnav, circa 2020