Reinforcement Learning. (3 h)

Introduction to reinforcement learning concepts and applications, including single-agent and multi-agent settings. Topics may cover value- and policy-based methods, temporal-difference learning, exploration strategies, explainability, and safety of learned agents. Students gain theoretical understanding and practical experience applying reinforcement learning techniques. P - CSC 270 .