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Probability Collectives A Distributed Multi-agent System Approach for Optimization /

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 techniqu...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Kulkarni, Anand Jayant (Autor), Tai, Kang (Autor), Abraham, Ajith (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2015.
Edición:1st ed. 2015.
Colección:Intelligent Systems Reference Library, 86
Temas:
Acceso en línea:Texto Completo

MARC

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100 1 |a Kulkarni, Anand Jayant.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
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. 
250 |a 1st ed. 2015. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2015. 
300 |a IX, 157 p. 68 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
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490 1 |a Intelligent Systems Reference Library,  |x 1868-4408 ;  |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. 
650 0 |a Computational intelligence. 
650 0 |a Artificial intelligence. 
650 0 |a System theory. 
650 0 |a Mathematical physics. 
650 1 4 |a Computational Intelligence. 
650 2 4 |a Artificial Intelligence. 
650 2 4 |a Complex Systems. 
650 2 4 |a Theoretical, Mathematical and Computational Physics. 
700 1 |a Tai, Kang.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Abraham, Ajith.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
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776 0 8 |i Printed edition:  |z 9783319160016 
776 0 8 |i Printed edition:  |z 9783319159997 
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830 0 |a Intelligent Systems Reference Library,  |x 1868-4408 ;  |v 86 
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912 |a ZDB-2-SXE 
950 |a Engineering (SpringerNature-11647) 
950 |a Engineering (R0) (SpringerNature-43712)