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Reinforcement Learning Series: Overview of Methods

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Steve Brunton

This video introduces the variety of methods for modelbased and modelfree reinforcement learning, including: dynamic programming, value and policy iteration, Qlearning, deep RL, TDlearning, SARSA, policy gradient optimization, among others.

Citable link for this video: https://doi.org/10.52843/cassyni.jcgdvc

This is the overview in a series on reinforcement learning, following the new Chapter 11 from the 2nd edition of our book "DataDriven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Brunton and Kutz

Book Website: http://databookuw.com
Book PDF: http://databookuw.com/databook.pdf
RL Chapter: https://faculty.washington.edu/sbrunt...

Amazon: https://www.amazon.com/DataDrivenSc...

Brunton Website: eigensteve.com

This video was produced at the University of Washington

posted by escoliatx8


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