香蕉视频

McGill.ca / Vue d'ensemble / Tous les cours

COMP 579 Reinforcement Learning (4 unit茅s)

Offered by: Informatique (Sciences)

Vue d'ensemble

Informatique (Sci) : Bandit algorithms, finite Markov decision processes, dynamic programming, Monte-Carlo Methods, temporal-difference learning, bootstrapping, planning, approximation methods, on versus off policy learning, policy gradient methods temporal abstraction and inverse reinforcement learning.

Terms: Hiver 2025

Instructors: Precup, Doina; Pr茅mont-Schwarz, Isabeau (Winter)

  • Prerequisite: A university level course in machine learning such as COMP 451 or COMP 551. Background in calculus, linear algebra, probability at the level of MATH 222, MATH 223, MATH 323, respectively.

Back to top