Reinforcement Learning Reinforcement learning studies methods for learning to act optimally based on the reward or punishment over time. Such machine learning is useful when we wish to learn high-quality behavior under uncertainty and the only data are reward signals. Introduces classical and modern methods in single- and multi-agent settings. Not offered on a regular basis. Credit Hours: 3 Prerequisites: CSCI(PHIL) 4550/6550 Level: Graduate Undergraduate
