Explore policy iteration in reinforcement learning through this comprehensive lecture. Delve into the fundamentals of policy optimization, understand the algorithm's workings with practical examples, and examine concepts such as monotonic improvement and convergence. Gain insights into modified policy iteration and analyze the complexity of the algorithm. Enhance your understanding of advanced reinforcement learning techniques and their applications in decision-making processes.
Overview
Syllabus
Intro
Policy Optimization
Algorithm
Example (Policy Iteration)
Monotonic Improvement
Convergence
Modified Policy Iteration
Complexity
Taught by
Pascal Poupart
