Csaba Szepesvari, PhD

Professor, Faculty of Science - Computing Science

Winter Term 2023 (1820)

CMPUT 365 - Introduction to Reinforcement Learning

★ 3 (fi 6)(EITHER, 3-0-0)

This course provides an introduction to reinforcement learning, which focuses on the study and design of learning agents that interact with a complex, uncertain world to achieve a goal. The course will cover multi- armed bandits, Markov decision processes, reinforcement learning, planning, and function approximation (online supervised learning). The course will take an information-processing approach to the study of intelligence and briefly touch on perspectives from psychology, neuroscience, and philosophy. The course will use the University of Alberta MOOC on Reinforcement Learning. Any student who understands the material in this course will understand the foundations of much of modern probabilistic artificial intelligence (AI) and be prepared to take more advanced courses, or to apply AI tools and ideas to real-world problems. Prerequisites: CMPUT 175 or 275; one of CMPUT 267, 466, or STAT 265; or consent of the instructor.

LECTURE B1 (47044)

2023-01-05 - 2023-04-12
MWF 13:00 - 13:50 (CAB 235)

CMPUT 605 - Topics in Computing Science

★ 3 (fi 6)(EITHER, 3-0-0)

LECTURE B01 (44364)

LECTURE B24 (50259)

LECTURE B29 (50277)