Reinforcement Learning and Markov Decision Precesses

3 Credits

Formal model based on Markov decision processes for automated learning from interactions with stochastic, incompletely known environments. Markov decision processes, dynamic programming, temporal-difference learning, Monte Carlo reinforcement learning methods. Credit will not be given for both CSE 337 and CSE 437 . Must have graduate standing in Computer Science or have consent of instructor.