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Memorias de investigación
Communications at congresses:
Migrating Individuals and Probabilistic Models on DEDAS: a Comparison on Continuous Functions
Year:2010
Research Areas
  • Artificial intelligence
Information
Abstract
One of the most promising areas in which probabilisticgraphical models have shown an incipient activity is thefield of heuristic optimization and, in particular, in the Estimationof Distribution Algorithms (EDAs). EDAs constitutea well-known family of Evolutionary Computationtechniques, similar to Genetic Algorithms. Due to their inherentparallelism, different research lines have been studiedtrying to improve EDAs from the point of view of executiontime and/or accuracy. Among these proposals, wefocus on the so-called island-based models. This approachdefines several islands (EDA instances) running independentlyand exchanging information with a given frequency.The information sent by the islands can be a set of individualsor a probabilistic model. This paper presents a comparativestudy of both information exchanging techniquesfor a univariate EDA (UMDAg) over a wide set of parametersand problems ¿the standard benchmark developed forthe IEEEWorkshop on Evolutionary Algorithms and otherMetaheuristics for Continuous Optimization Problems ofthe ISDA 2009 Conference. The study concludes that theconfigurations based on migrating individuals obtain betterresults.
International
No
Congress
Proceedings of the Tenth IASTED International Conference on Artificial Intelligence and Applications (2010)
960
Place
Reviewers
Si
ISBN/ISSN
978-0-88986-818-2
Start Date
15/02/2010
End Date
17/02/2010
From page
255
To page
262
Migrating Individuals and Probabilistic Models on DEDAS: a Comparison on Continuous Functions
Participants
  • Autor: Santiago Muelas Pascual (UPM)
  • Autor: Antonio Latorre De la Fuente (UPM)
  • Autor: Jose Maria Peña Sanchez (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: COMPUTATIONAL INTELLIGENCE GROUP
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