Reinforcement Learning Series: Overview of Methods

This video introduces the variety of methods for model-based and model-free reinforcement learning, including: dynamic programming, value and policy iteration, Q-learning, deep RL, TD-learning, SARSA, policy gradient optimization, among others. This is the overview in a series on reinforcement learning, following the new Chapter 11 from the 2nd edition of our book “Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control“ by Brunton and Kutz Book Website: Book PDF: Amazon: Brunton Website: