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Multi-agent machine learning = a rei...

Schwartz, Howard M.

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Multi-agent machine learning = a reinforcement approach /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Multi-agent machine learning/ Howard M. Schwartz.
其他題名:	a reinforcement approach /
作者:	Schwartz, Howard M.
出版者:	Hoboken, New Jersey :Wiley, : 2014.,
面頁冊數:	1 online resource (xi, 242 p.)
標題:	Reinforcement learning. -
電子資源:	http://onlinelibrary.wiley.com/book/10.1002/9781118884614
ISBN:	9781118884614

Multi-agent machine learning = a reinforcement approach /
Schwartz, Howard M.

Multi-agent machine learninga reinforcement approach /[electronic resource] :Howard M. Schwartz. - Hoboken, New Jersey :Wiley,2014. - 1 online resource (xi, 242 p.)

Includes bibliographical references and index.

"Multi-Agent Machine Learning: A Reinforcement Learning Approach is a framework to understanding different methods and approaches in multi-agent machine learning. It also provides cohesive coverage of the latest advances in multi-agent differential games and presents applications in game theory and robotics. 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"--

ISBN: 9781118884614

LCCN: 2014021985Subjects--Topical Terms:

1006373
Reinforcement learning.

LC Class. No.: Q325.6 / .S39 2014

Dewey Class. No.: 519.3

Multi-agent machine learning = a reinforcement approach /
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245 1 0 $a Multi-agent machine learning $h [electronic resource] : $b a reinforcement approach / $c Howard M. Schwartz.
260 $a Hoboken, New Jersey : $b Wiley, $c 2014.
300 $a 1 online resource (xi, 242 p.)
504 $a Includes bibliographical references and index.
520 $a "Multi-Agent Machine Learning: A Reinforcement Learning Approach is a framework to understanding different methods and approaches in multi-agent machine learning. It also provides cohesive coverage of the latest advances in multi-agent differential games and presents applications in game theory and robotics. 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"-- $c Provided by publisher.
520 $a "Provide an in-depth coverage of multi-player, differential games and Gam theory"-- $c Provided by publisher.
588 0 $a Online resource; title from digital title page (viewed on December 2, 2014).
650 0 $a Reinforcement learning. $3 1006373
650 0 $a Differential games. $3 596345
650 0 $a Swarm intelligence. $3 577800
650 0 $a Machine learning. $3 533906
856 4 0 $u http://onlinelibrary.wiley.com/book/10.1002/9781118884614