CSCI 265 - Reinforcement Learning

Prerequisite: CSCI 115 or permission of instructor.
This course covers the concepts and current trends in reinforcement learning, including the theory of Markov decision processes, dynamic programming, temporal difference learning, Monte Carlo methods, and the role of function approximation. (Formerly CSCI 291T)

Units: 3

Course Typically Offered: Fall