Introduction to Reinforcement Learning

An introductory course in reinforcement learning, the branch of AI in which agents learn from repeated interaction with an environment. Students study Markov decision processes, dynamic programming, and value and policy iteration, then extend these ideas through temporal-difference methods, Monte Carlo techniques, and function approximation with neural networks.