A professor at the College of Science and Mathematics. Reinforcement learning and its applications to control and multi-agent systems is where his doctoral studies originated. In general terms, reinforcement learning is concerned with computational approaches to learning from reward. Here, he considers how a learning agent can learn as quickly as possible from limited interaction with other agents and its environment.