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dc.contributor.authorLuque-Polo, Gabriel Jesús 
dc.contributor.authorAlba-Torres, Enrique 
dc.date.accessioned2013-07-15T10:12:44Z
dc.date.available2013-07-15T10:12:44Z
dc.date.issued2013
dc.identifier.citationG. Luque, E. Alba, Math Oracles: A New Way of Designing Efficient Self-Adaptive Algorithms, Proceedings of the Genetic and Evolutionary Computation Conference Companion,pp. 217-218, GECCO'13, July 6–10, 2013, Amsterdam, The Netherlands. ACM 2013, ISBN 978-1-4503-1964-5.es_ES
dc.identifier.urihttp://hdl.handle.net/10630/5612
dc.description.abstractIn this paper we present a new general methodology to develop self-adaptive methods at a low computational cost. Instead of going purely ad-hoc we de ne several simple steps to include theoretical models as additional information in our algorithm. Our idea is to incorporate the predictive information (future behavior) provided by well-known mathematical models or other prediction systems (the oracle) to build enhanced methods. We show the main steps which should be considered to include this new kind of information into any algorithm. In addition, we actually test the idea on a speci c algorithm, a genetic algorithm (GA). Experiments show that our proposal is able to obtain similar, or even better results when it is compared to the traditional algorithm. We also show the bene ts in terms of saving time and a lower complexity of parameter settings.es_ES
dc.description.sponsorshipUniversidad de Málaga. Proyecto roadME (TIN2011-28194)es_ES
dc.language.isoenges_ES
dc.publisherACM Presses_ES
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectLenguajes de programaciónes_ES
dc.subjectComputación evolutivaes_ES
dc.subjectAlgoritmos genéticoses_ES
dc.subject.otherMetaheuristicses_ES
dc.subject.otherTheoryes_ES
dc.subject.otherSelf-* algorithmses_ES
dc.titleMath Oracles: A New Way of Designing Efficient Self-Adaptive Algorithmses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.centroE.T.S.I. Informáticaes_ES


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