Description: Handbook of Reinforcement Learning and Control, Paperback by Vamvoudakis, Kyriakos G. (EDT); Wan, Yan (EDT); Lewis, Frank L. (EDT); Cansever, Derya (EDT), ISBN 3030609928, ISBN-13 9783030609924, Brand New, Free shipping in the US This handbook presents state-of-the-art research in reinforcement learning, focusing on its applications in the control and game theory of dynamic systems and future directions for related research and technology. The contributions gathered in this book deal with challenges faced when using learning and adaptation methods to solve academic and industrial problems, such as optimization in dynamic environments with single and multiple agents, convergence and performance analysis, and online implementation. They explore means by which these difficulties can be solved, and cover a wide range of related topics including: deep learning;artificial intelligence;applications of game theory;mixed modality learning; andmulti-agent reinforcement learning. Practicing engineers and scholars in the field of machine learning, game theory, and autonomous control will find the Handbook of Reinforcement Learning and Control to be thought-provoking, instructive and informative.
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End Time: 2024-12-24T12:14:30.000Z
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Book Title: Handbook of Reinforcement Learning and Control
Number of Pages: Xxiv, 833 Pages
Language: English
Publisher: Springer International Publishing A&G
Topic: Probability & Statistics / General, Intelligence (Ai) & Semantics, General, Electrical
Publication Year: 2022
Illustrator: Yes
Genre: Mathematics, Computers, Technology & Engineering, Science
Item Weight: 45.6 Oz
Author: Yan Wan
Item Length: 9.3 in
Item Width: 6.1 in
Book Series: Studies in Systems, Decision and Control Ser.
Format: Trade Paperback
