Using adaptive novelty search in differential evolution

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dc.contributor.authorFister, Iztok
dc.contributor.authorIglesias, Andres
dc.contributor.authorGalvez, Akemi
dc.contributor.authorDel Ser, Javier
dc.contributor.authorOsaba, Eneko
dc.contributor.authorFister, Iztok
dc.contributor.editorDe La Prieta, Fernando
dc.contributor.editorGonzález-Briones, Alfonso
dc.contributor.editorPawleski, Pawel
dc.contributor.editorCalvaresi, Davide
dc.contributor.editorDel Val, Elena
dc.contributor.editorJulian, Vicente
dc.contributor.editorLopes, Fernando
dc.contributor.editorOsaba, Eneko
dc.contributor.editorSánchez-Iborra, Ramón
dc.contributor.institutionIA
dc.contributor.institutionQuantum
dc.date.accessioned2024-07-24T11:46:24Z
dc.date.available2024-07-24T11:46:24Z
dc.date.issued2019
dc.descriptionPublisher Copyright: © Springer Nature Switzerland AG 2019.
dc.description.abstractNovelty search ensures evaluation of solutions in stochastic population-based nature-inspired algorithms according to additional measure, where each solution is evaluated by a distance to its neighborhood beside the fitness function. Thus, the population diversity is preserved that is a prerequisite for the open-ended evolution in evolutionary robotics. Recently, the Novelty search was applied for solving the global optimization into differential evolution, where all Novelty search parameters remain unchanged during the run. The novelty area width parameter, that determines the diameter specifying the minimum change in each direction needed the solution for treating as the novelty, has a crucial influence on the optimization results. In this study, this parameter was adapted during the evolutionary process. The proposed self-adaptive differential evolution using the adaptive Novelty search were applied for solving the CEC 2014 Benchmark function suite, and the obtained results confirmed the usefulness of the adaptation.en
dc.description.sponsorshipAcknowledgments. Iztok Fister and Iztok Fister Jr. acknowledge the financial support from the Slovenian Research Agency (Research Core Fundings No. P2-0041 and P2-0057). Javier Del Ser and Eneko Osaba would like to thank the Basque Government for its funding support through the EMAITEK program.
dc.description.statusPeer reviewed
dc.format.extent9
dc.identifier.citationFister , I , Iglesias , A , Galvez , A , Del Ser , J , Osaba , E & Fister , I 2019 , Using adaptive novelty search in differential evolution . in F De La Prieta , A González-Briones , P Pawleski , D Calvaresi , E Del Val , V Julian , F Lopes , E Osaba & R Sánchez-Iborra (eds) , Highlights of Practical Applications of Survivable Agents and Multi-Agent Systems. The PAAMS Collection - International Workshops of PAAMS 2019, Proceedings . Communications in Computer and Information Science , vol. 1047 , Springer Verlag , pp. 267-275 , 17th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2019 , Ávila , Spain , 26/06/19 . https://doi.org/10.1007/978-3-030-24299-2_23
dc.identifier.citationconference
dc.identifier.doi10.1007/978-3-030-24299-2_23
dc.identifier.isbn9783030242985
dc.identifier.issn1865-0929
dc.identifier.urihttps://hdl.handle.net/11556/1557
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85068623587&partnerID=8YFLogxK
dc.language.isoeng
dc.publisherSpringer Verlag
dc.relation.ispartofHighlights of Practical Applications of Survivable Agents and Multi-Agent Systems. The PAAMS Collection - International Workshops of PAAMS 2019, Proceedings
dc.relation.ispartofseriesCommunications in Computer and Information Science
dc.relation.projectIDEusko Jaurlaritza
dc.relation.projectIDJavna Agencija za Raziskovalno Dejavnost RS, ARRS
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsAdaptive Novelty search
dc.subject.keywordsDifferential evolution
dc.subject.keywordsEvolutionary robotics
dc.subject.keywordsOpen-ended evolution
dc.subject.keywordsGeneral Computer Science
dc.subject.keywordsGeneral Mathematics
dc.titleUsing adaptive novelty search in differential evolutionen
dc.typeconference output
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