Control Systems and Reinforcement Learning (Hardcover)

Language: English

Published by Cambridge University Press, Cambridge, 2022

1316511960 / 9781316511961

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Hardcover. A high school student can create deep Q-learning code to control her robot, without any understanding of the meaning of 'deep' or 'Q', or why the code sometimes fails. This book is designed to explain the science behind reinforcement learning and optimal control in a way that is accessible to students with a background in calculus and matrix algebra. A unique focus is algorithm design to obtain the fastest possible speed of convergence for learning algorithms, along with insight into why reinforcement learning sometimes fails. Advanced stochastic process theory is avoided at the start by substituting random exploration with more intuitive deterministic probing for learning. Once these ideas are understood, it is not difficult to master techniques rooted in stochastic control. These topics are covered in the second part of the book, starting with Markov chain theory and ending with a fresh look at actor-critic methods for reinforcement learning. The book is written for newcomers to reinforcement learning who wish to write code for various applications, from robotics to power systems to supply chains. It also contains advanced material designed to prepare graduate students and professionals for both research and application of reinforcement learning and optimal control techniques. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Seller Inventory # 9781316511961

Title
Control Systems and Reinforcement Learning (Hardcover)
Author
Sean Meyn
Publisher
Cambridge University Press, Cambridge
Publication year
2022
Condition
new
Binding
Hardcover
Language
English
ISBN 10
1316511960
ISBN 13
9781316511961

CitiRetail

Stevenage, United Kingdom

5-star seller

AbeBooks seller since June 29, 2022

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