The first class takes place Monday, January 6, 2022, on zoom. You can find the zoom link for the lectures as well as for Doina's office hours in MyCourses. As McGill has announced, courses will be online at least until January 24. The delivery method after that date remains to be determined based on the university's decision, but the course will be recorded throughout the term.
When: Tuesday and Thursday, 2:35-3:55pm
What: The goal of this class is to provide an introduction to reinforcement learning, a very active sub-field of machine learning. Reinforcement learning is concerned with building programs that learn how to predict and act in a stochastic, dynamic environment, based on past experience. Applications of reinforcement learning range from classical control problems, such as powerplant optimization or dynamical system control, to game playing, inventory control, and many other fields. Notably, reinforcement learning has also produced very compelling models of animal and human learning. During this course, we will study theoretical properties and practical applications of reinforcement leanring. We will start by following the second edition of the classic textbook by Sutton & Barto (available online), but we will supplement it with papers and other materials.
Doina Precup
School of Computer Science
Office Hours: Tuesday and Thursday, 4:00-5:00pm
E-mail: dprecup@cs.mcgill.ca
To be added
MyCourses will be used for bulletin board, discussion groups, assignment submission and grading.