Reinforcement Learning Series - Overview of Methods

Explore an overview of various reinforcement learning methods in this 22-minute video lecture. Dive into both model-based and model-free approaches, including dynamic programming, value and policy iteration, Q-learning, deep reinforcement learning, TD-learning, SARSA, and policy gradient optimization. Gain insights from the new Chapter 11 of the second edition of "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Brunton and Kutz. Access additional resources, including the book's website, PDF, and Amazon link, to further enhance your understanding of reinforcement learning concepts and applications.

Reinforcement Learning Series: Overview of Methods