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Probability collectives = a distribu...

Kulkarni, Anand Jayant.

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Probability collectives = a distributed multi-agent system approach for optimization /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Probability collectives/ by Anand Jayant Kulkarni, Kang Tai, Ajith Abraham.
Reminder of title:	a distributed multi-agent system approach for optimization /
Author:	Kulkarni, Anand Jayant.
other author:	Tai, Kang.
Published:	Cham :Springer International Publishing : : 2015.,
Description:	ix, 157 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction to Optimization -- Probability Collectives: A Distributed Optimization Approach -- Constrained Probability Collectives: A Heuristic Approach -- Constrained Probability Collectives with a Penalty Function Approach -- Constrained Probability Collectives With Feasibility-Based Rule I -- Probability Collectives for Discrete and Mixed Variable Problems -- Probability Collectives with Feasibility-Based Rule II.
Contained By:	Springer eBooks
Subject:	Multiagent systems. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-16000-9
ISBN:	9783319160009 (electronic bk.)

Probability collectives = a distributed multi-agent system approach for optimization /
Kulkarni, Anand Jayant.

Probability collectivesa distributed multi-agent system approach for optimization /[electronic resource] :by Anand Jayant Kulkarni, Kang Tai, Ajith Abraham. - Cham :Springer International Publishing :2015. - ix, 157 p. :ill., digital ;24 cm. - Intelligent systems reference library,v.861868-4394 ;. - Intelligent systems reference library ;v.24..

Introduction to Optimization -- Probability Collectives: A Distributed Optimization Approach -- Constrained Probability Collectives: A Heuristic Approach -- Constrained Probability Collectives with a Penalty Function Approach -- Constrained Probability Collectives With Feasibility-Based Rule I -- Probability Collectives for Discrete and Mixed Variable Problems -- Probability Collectives with Feasibility-Based Rule II.

This book provides an emerging computational intelligence tool in the framework of collective intelligence for modeling and controlling distributed multi-agent systems referred to as Probability Collectives. In the modified Probability Collectives methodology a number of constraint handling techniques are incorporated, which also reduces the computational complexity and improved the convergence and efficiency. Numerous examples and real world problems are used for illustration, which may also allow the reader to gain further insight into the associated concepts.

ISBN: 9783319160009 (electronic bk.)

Standard No.: 10.1007/978-3-319-16000-9doiSubjects--Topical Terms:

1048048
Multiagent systems.

LC Class. No.: QA76.76.I58

Dewey Class. No.: 006.3

Probability collectives = a distributed multi-agent system approach for optimization /
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100 1 $a Kulkarni, Anand Jayant. $3 2134699
245 1 0 $a Probability collectives $h [electronic resource] : $b a distributed multi-agent system approach for optimization / $c by Anand Jayant Kulkarni, Kang Tai, Ajith Abraham.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a ix, 157 p. : $b ill., digital ; $c 24 cm.
490 1 $a Intelligent systems reference library, $x 1868-4394 ; $v v.86
505 0 $a Introduction to Optimization -- Probability Collectives: A Distributed Optimization Approach -- Constrained Probability Collectives: A Heuristic Approach -- Constrained Probability Collectives with a Penalty Function Approach -- Constrained Probability Collectives With Feasibility-Based Rule I -- Probability Collectives for Discrete and Mixed Variable Problems -- Probability Collectives with Feasibility-Based Rule II.
520 $a This book provides an emerging computational intelligence tool in the framework of collective intelligence for modeling and controlling distributed multi-agent systems referred to as Probability Collectives. In the modified Probability Collectives methodology a number of constraint handling techniques are incorporated, which also reduces the computational complexity and improved the convergence and efficiency. Numerous examples and real world problems are used for illustration, which may also allow the reader to gain further insight into the associated concepts.
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650 2 4 $a Artificial Intelligence (incl. Robotics). $3 923876
650 2 4 $a Statistical Physics, Dynamical Systems and Complexity. $3 1066325
700 1 $a Tai, Kang. $3 2134700
700 1 $a Abraham, Ajith. $3 891046
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