MIE567H1

Multi-agent Reinforcement Learning

This course is to provide fundamental concepts and mathematical frameworks for sequential decision making of a team of decision makers in the presence of uncertainty. Topics include Markov decision processes, reinforcement learning, theory of games and stochastic games, multi-agent reinforcement learning and decentralized Markov decision processes. The course places an emphasize on conceptual understanding of core concepts and expects students to be able to implement the concepts to demonstrate their understanding.