Multi-Agent Machine Learning

Schwartz

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Language: English

Published by John Wiley & Sons Aug 2014, 2014

111836208X / 9781118362082

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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Neuware - The book begins with a chapter on traditional methods of supervised learning, covering recursive least squares learning, mean square error methods, and stochastic approximation. Chapter 2 covers single agent reinforcement learning. Topics include learning value functions, Markov games, and TD learning with eligibility traces. Chapter 3 discusses two player games including two player matrix games with both pure and mixed strategies. Numerous algorithms and examples are presented. Chapter 4 covers learning in multi-player games, stochastic games, and Markov games, focusing on learning multi-player grid games--two player grid games, Q-learning, and Nash Q-learning. Chapter 5 discusses differential games, including multi player differential games, actor critique structure, adaptive fuzzy control and fuzzy interference systems, the evader pursuit game, and the defending a territory games. Chapter 6 discusses new ideas on learning within robotic swarms and the innovative idea of the evolution of personality traits.\* Framework for understanding a variety of methods and approaches in multi-agent machine learning.\* Discusses methods of reinforcement learning such as a number of forms of multi-agent Q-learning\* Applicable to research professors and graduate students studying electrical and computer engineering, computer science, and mechanical and aerospace engineering.…

Seller Inventory # 9781118362082

Title
Multi-Agent Machine Learning
Author
Schwartz
Publisher
John Wiley & Sons Aug 2014
Publication year
2014
Condition
Neu
Binding
Buch
Language
English
ISBN 10
111836208X
ISBN 13
9781118362082
Item weight
554 grams
Dimensions
240x161x18 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

Shipping rates from Germany to U.S.A.

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