Introduction to Reinforcement Learning

An introductory course on reinforcement learning that keeps the mathematics deliberately light, building up from Markov decision processes to the field's main algorithmic families: model-based, value-based, and policy-based learning. Students also examine modern challenges and open problems that shape current reinforcement-learning research.