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dc.contributor.authorCruz Echeandía, Marina de la
dc.contributor.authorMartín Lázaro, Alba
dc.contributor.authorOrtega de la Puente, Alfonso
dc.contributor.authorMontaña Arnaiz, José Luis 
dc.contributor.authorAlonso González, César Luis
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2023-04-20T12:59:50Z
dc.date.available2023-04-20T12:59:50Z
dc.date.issued2010
dc.identifier.isbn978-989-8425-31-7
dc.identifier.otherTIN2007-67466-C02-02es_ES
dc.identifier.urihttps://hdl.handle.net/10902/28556
dc.description.abstractThis paper is focused on two different approaches (previously proposed by the authors) that perform better than Genetic Programming in typical symbolic regression problems: straight-line program genetic programming (SLP-GP) and evolution with attribute grammars (AGE). Both approaches have different characteristics. One of themost important is that SLP-GP keeps semantic blocks invariant (the crossover operator always exchanges complete subexpressions). In this paper we compare both methods and study the possible effect on their performance of keeping these blocks invariant.es_ES
dc.description.sponsorshipThis work was partially supported by the R&D program of the Community of Madrid (S2009/TIC-1650, project “e-Madrid”) as well as by the Spanish Ministry of Science and Innovation (TIN2007-67466-C02-02). The authors thank Dr. Manuel Alfonseca for his help to prepare this document.es_ES
dc.format.extent4 p.es_ES
dc.language.isoenges_ES
dc.publisherScitePress, Science and Technology Publications, Ldaes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationales_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceICEC 2010 : International Conference on Evolutionary Computation : proceedings : Valencia, Spain, 24-26 October 2010, Setúbal, SciTePress, 2010es_ES
dc.subject.otherGrammar evolutiones_ES
dc.subject.otherAttribute grammarses_ES
dc.subject.otherChristiansen grammarses_ES
dc.subject.otherGenetic programminges_ES
dc.subject.otherStraight-line programses_ES
dc.subject.otherSymbolic regressiones_ES
dc.titleThe role of keeping "semantic blocks" invariant: effects in linear genetic programming performancees_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.relation.publisherVersionhttps://doi.org/10.5220/0003085403650368es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.5220/0003085403650368
dc.type.versionpublishedVersiones_ES


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Attribution-NonCommercial-NoDerivatives 4.0 InternationalExcepto si se señala otra cosa, la licencia del ítem se describe como Attribution-NonCommercial-NoDerivatives 4.0 International