demonstration

An agent-based collaborative evolutionary model for multimodal optimization

Authors:

Rodica I. Lung,

D. DumitrescuAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference companion on Genetic and evolutionary computation

Pages 1969 - 1976

https://doi.org/10.1145/1388969.1389008

Published: 12 July 2008 Publication History

Abstract

A novel approach to multimodal optimization called Roaming Agent-Based Collaborative Evolutionary Model (RACE) combining several evolutionary techniques with agent-based modeling is proposed. RACE model aims to detect multiple global and local optima by training a multi-agent system to employ various evolutionary techniques suitable for a specified multimodal optimization problem. Agents can exchange information during the search process enabling a cooperative search of optima between several populations evolving independently. Redundant search by multiple agents is avoided by having them communicate and negotiate about the space region searched. An agent can request and receive from another agent valuable information and genetic material for a better search of a certain region in the environment. Performance of the proposed agent-based collaborative evolutionary model is compared by means of numerical experiments with rival evolutionary techniques.

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Cited By

Wong KWu CMok RPeng CZhang Z(2012)Evolutionary multimodal optimization using the principle of localityInformation Sciences: an International Journal10.1016/j.ins.2011.12.016194(138-170)Online publication date: 1-Jul-2012
https://dl.acm.org/doi/10.1016/j.ins.2011.12.016
Wong KLeung KWong M(2010)Effect of spatial locality on an evolutionary algorithm for multimodal optimizationProceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I10.1007/978-3-642-12239-2_50(481-490)Online publication date: 7-Apr-2010
https://dl.acm.org/doi/10.1007/978-3-642-12239-2_50
Wong KLeung KWong MRothlauf F(2009)An evolutionary algorithm with species-specific explosion for multimodal optimizationProceedings of the 11th Annual conference on Genetic and evolutionary computation10.1145/1569901.1570027(923-930)Online publication date: 8-Jul-2009
https://dl.acm.org/doi/10.1145/1569901.1570027
Show More Cited By

Index Terms

An agent-based collaborative evolutionary model for multimodal optimization
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Intelligent agents
      2. Multi-agent systems
    2. Search methodologies
      1. Heuristic function construction

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cover image ACM Conferences

GECCO '08: Proceedings of the 10th annual conference companion on Genetic and evolutionary computation

July 2008

1182 pages

ISBN:9781605581316

DOI:10.1145/1388969

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

Copyright © 2008 ACM.

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Published: 12 July 2008

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GECCO08: Genetic and Evolutionary Computation Conference

July 12 - 16, 2008

GA, Atlanta, USA

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Wong KWu CMok RPeng CZhang Z(2012)Evolutionary multimodal optimization using the principle of localityInformation Sciences: an International Journal10.1016/j.ins.2011.12.016194(138-170)Online publication date: 1-Jul-2012
https://dl.acm.org/doi/10.1016/j.ins.2011.12.016
Wong KLeung KWong M(2010)Effect of spatial locality on an evolutionary algorithm for multimodal optimizationProceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I10.1007/978-3-642-12239-2_50(481-490)Online publication date: 7-Apr-2010
https://dl.acm.org/doi/10.1007/978-3-642-12239-2_50
Wong KLeung KWong MRothlauf F(2009)An evolutionary algorithm with species-specific explosion for multimodal optimizationProceedings of the 11th Annual conference on Genetic and evolutionary computation10.1145/1569901.1570027(923-930)Online publication date: 8-Jul-2009
https://dl.acm.org/doi/10.1145/1569901.1570027
Bastani BGreaves D(2009)Complex open-system design by quasi-agentsACM SIGSOFT Software Engineering Notes10.1145/1543405.154341234:4(1-14)Online publication date: 6-Jul-2009
https://dl.acm.org/doi/10.1145/1543405.1543412

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