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Exploring population geometry and multi-agent systems: a new approach to developing evolutionary techniques

Authors:

Camelia Chira,

Anca Gog,

D. DumitrescuAuthors Info & Claims

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

Pages 1953 - 1960

https://doi.org/10.1145/1388969.1389006

Published: 12 July 2008 Publication History

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Abstract

Evolutionary algorithms require efficient recombination and selection mechanisms in order to produce high-quality solutions. In order to guide recombination a geometrical structure of the population is introduced. The aim of this paper is to explore connections between population geometry and individual interactions inducing autonomy, communication and reactivity. Each individual in the population acts as an autonomous agent with the goal of optimizing its fitness. In this process, each individual is able to communicate and select a mate for recombination. The introduced paradigm is illustrated by an evolutionary technique relying on a new population model and agent-based selection for recombination strategy. Search operators are asynchronously applied making the proposed approach more realistic. Numerical experiments indicate the potential of the proposed evolutionary agent-driven technique.

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Cited By

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de Carvalho VSichman J(2019)Evolutionary Computation Meets Multiagent Systems for Better Solving Optimization ProblemsEvolutionary Computing and Artificial Intelligence10.1007/978-981-13-6936-0_4(27-41)Online publication date: 14-Mar-2019
https://doi.org/10.1007/978-981-13-6936-0_4
Byrski ASchaefer RSmołka MCotta C(2010)Asymptotic analysis of computational multi-agent systemsProceedings of the 11th international conference on Parallel problem solving from nature: Part I10.5555/1885031.1885083(475-484)Online publication date: 11-Sep-2010
https://dl.acm.org/doi/10.5555/1885031.1885083
Barkat Ullah ASarker RLokan C(2010)Handling equality constraints with agent-based memetic algorithmsMemetic Computing10.1007/s12293-010-0051-63:1(51-72)Online publication date: 6-Oct-2010
https://doi.org/10.1007/s12293-010-0051-6
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Exploring population geometry and multi-agent systems: a new approach to developing evolutionary techniques

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Published In

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

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

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

View all

de Carvalho VSichman J(2019)Evolutionary Computation Meets Multiagent Systems for Better Solving Optimization ProblemsEvolutionary Computing and Artificial Intelligence10.1007/978-981-13-6936-0_4(27-41)Online publication date: 14-Mar-2019
https://doi.org/10.1007/978-981-13-6936-0_4
Byrski ASchaefer RSmołka MCotta C(2010)Asymptotic analysis of computational multi-agent systemsProceedings of the 11th international conference on Parallel problem solving from nature: Part I10.5555/1885031.1885083(475-484)Online publication date: 11-Sep-2010
https://dl.acm.org/doi/10.5555/1885031.1885083
Barkat Ullah ASarker RLokan C(2010)Handling equality constraints with agent-based memetic algorithmsMemetic Computing10.1007/s12293-010-0051-63:1(51-72)Online publication date: 6-Oct-2010
https://doi.org/10.1007/s12293-010-0051-6
Byrski ASchaefer RSmołka MCotta C(2010)Asymptotic Analysis of Computational Multi-Agent SystemsParallel Problem Solving from Nature, PPSN XI10.1007/978-3-642-15844-5_48(475-484)Online publication date: 2010
https://doi.org/10.1007/978-3-642-15844-5_48
Ullah ASarker RLokan C(2010)An Agent Based Evolutionary Approach for Nonlinear Optimization with Equality ConstraintsAgent-Based Evolutionary Search10.1007/978-3-642-13425-8_3(49-76)Online publication date: 2010
https://doi.org/10.1007/978-3-642-13425-8_3
Gog AChira CDumitrescu D(2009)Asynchronous evolutionary searchProceedings of the Eleventh conference on Congress on Evolutionary Computation10.5555/1689599.1689631(240-246)Online publication date: 18-May-2009
https://dl.acm.org/doi/10.5555/1689599.1689631
Ullah ASarker RLokan C(2009)An agent-based memetic algorithm (AMA) for nonlinear optimization with equality constraintsProceedings of the Eleventh conference on Congress on Evolutionary Computation10.5555/1689599.1689609(70-77)Online publication date: 18-May-2009
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Chira CGog ADumitrescu DRothlauf F(2009)Asynchronous collaborative search using adaptive co-evolving subpopulationsProceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers10.1145/1570256.1570364(2575-2582)Online publication date: 8-Jul-2009
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Gog AChira CDumitrescu D(2009)Asynchronous evolutionary search: Multi-population collaboration and complex dynamics2009 IEEE Congress on Evolutionary Computation10.1109/CEC.2009.4982954(240-246)Online publication date: May-2009
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Barkat Ullah ASarker RLokan C(2009)An Agent-based Memetic Algorithm (AMA) for nonlinear optimization with equality constraints2009 IEEE Congress on Evolutionary Computation10.1109/CEC.2009.4982932(70-77)Online publication date: May-2009
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