Reinforcement Learning and its Application in Games

Abstract

This thesis starts by describing the fundamentals of reinforcement learning and various algorithms that it uses while emphasizing its recent revolution with deep learning. I implemented a subset of these methods and used them in different configurations for training intelligent agents to play the game of checkers in a self-play mode. Both standard and deep learning agents are compared, and the results are presented at the end of this paper.