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Evolutionary multi-agent systems = f...
~
Byrski, Aleksander.
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Evolutionary multi-agent systems = from inspirations to applications /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Evolutionary multi-agent systems/ by Aleksander Byrski, Marek Kisiel-Dorohinicki.
Reminder of title:
from inspirations to applications /
Author:
Byrski, Aleksander.
other author:
Kisiel-Dorohinicki, Marek.
Published:
Cham :Springer International Publishing : : 2017.,
Description:
xiv, 210 p. :ill., digital ;24 cm.
[NT 15003449]:
Preface -- Part I Concept and formal model: Contemporary methods of computational intelligence -- Agent-based computing -- Formal aspects of agent-based metaheuristics -- Part II Design and implementation: Agent-based and component inspirations -- Implementation aspects of agent-based computing systems -- AgE Computing Environment -- Part III Experimental results: EMAS in optimization problems -- Tuning of EMAS parameters -- Final remarks -- References.
Contained By:
Springer eBooks
Subject:
Multiagent systems. -
Online resource:
http://dx.doi.org/10.1007/978-3-319-51388-1
ISBN:
9783319513881
Evolutionary multi-agent systems = from inspirations to applications /
Byrski, Aleksander.
Evolutionary multi-agent systems
from inspirations to applications /[electronic resource] :by Aleksander Byrski, Marek Kisiel-Dorohinicki. - Cham :Springer International Publishing :2017. - xiv, 210 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.6801860-949X ;. - Studies in computational intelligence ;v.680..
Preface -- Part I Concept and formal model: Contemporary methods of computational intelligence -- Agent-based computing -- Formal aspects of agent-based metaheuristics -- Part II Design and implementation: Agent-based and component inspirations -- Implementation aspects of agent-based computing systems -- AgE Computing Environment -- Part III Experimental results: EMAS in optimization problems -- Tuning of EMAS parameters -- Final remarks -- References.
This book addresses agent-based computing, concentrating in particular on evolutionary multi-agent systems (EMAS), which have been developed since 1996 at the AGH University of Science and Technology in Cracow, Poland. It provides the relevant background information on and a detailed description of this computing paradigm, along with key experimental results. Readers will benefit from the insightful discussion, which primarily concerns the efficient implementation of computing frameworks for developing EMAS and similar computing systems, as well as a detailed formal model. Theoretical deliberations demonstrating that computing with EMAS always helps to find the optimal solution are also included, rounding out the coverage.
ISBN: 9783319513881
Standard No.: 10.1007/978-3-319-51388-1doiSubjects--Topical Terms:
1048048
Multiagent systems.
LC Class. No.: QA76.76.I58
Dewey Class. No.: 006.3
Evolutionary multi-agent systems = from inspirations to applications /
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Preface -- Part I Concept and formal model: Contemporary methods of computational intelligence -- Agent-based computing -- Formal aspects of agent-based metaheuristics -- Part II Design and implementation: Agent-based and component inspirations -- Implementation aspects of agent-based computing systems -- AgE Computing Environment -- Part III Experimental results: EMAS in optimization problems -- Tuning of EMAS parameters -- Final remarks -- References.
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This book addresses agent-based computing, concentrating in particular on evolutionary multi-agent systems (EMAS), which have been developed since 1996 at the AGH University of Science and Technology in Cracow, Poland. It provides the relevant background information on and a detailed description of this computing paradigm, along with key experimental results. Readers will benefit from the insightful discussion, which primarily concerns the efficient implementation of computing frameworks for developing EMAS and similar computing systems, as well as a detailed formal model. Theoretical deliberations demonstrating that computing with EMAS always helps to find the optimal solution are also included, rounding out the coverage.
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Engineering (Springer-11647)
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EB QA76.76.I58
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