CS885 Reinforcement Learning - Spring 2020

Learn advanced reinforcement learning concepts through this comprehensive university lecture series covering trust region and proximal policy optimization methods, maximum entropy reinforcement learning approaches, and imitation learning techniques, with detailed coverage of course logistics, assignments, critiques, presentations, and project requirements for graduate-level study.

Syllabus

CS885 Spring-20 Welcome & Logistics
CS885 Spring-20 Goals
CS885 Spring-20 Schedule
CS885 Spring-20 Marks
CS885 Spring-20 Assignments
CS885 Spring-20 Critiques
CS885 Spring-20 Presentation
CS885 Spring-20 Project
CS885 Module 1: Trust region & proximal policy optimization
CS885 Module 2: Maximum Entropy Reinforcement Learning
CS885 Module 3: Imitation Learning