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dc.contributor.authorHill, Seamus
dc.contributor.authorO'Riordan, Colm
dc.date.accessioned2018-12-07T12:40:38Z
dc.date.available2018-12-07T12:40:38Z
dc.date.issued2016
dc.identifier.citationHill, Seamus, & O'Riordan, Colm. (2016). Diversifying techniques and neutrality in genetic algorithms. Paper presented at the 8th International Conference on Evolutionary Computation Theory and Applications ECTA, Porto, Portugal, In Proceedings of the 8th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2016) ISBN 978-989-758-201-1, pages 140-147. DOI: 10.5220/0006036201400147en_IE
dc.identifier.isbn978-989-758-201-1
dc.identifier.urihttp://hdl.handle.net/10379/14676
dc.description.abstractThis paper examines the implicit maintenance of diversity within a population through the inclusion of a layered genotype-phenotype map (GP-map) in a Genetic Algorithm (GA), based on the principal of Neutral theory. The paper compares a simple GA (SGA), incorporating a variety of diversifying techniques, to the multi-layered GA (MGA) as proposed by the authors. The MGA creates a neutral representation by including a layered GP-map based on the biological concepts of Transcription and Translation. In standard GAs, each phenotype is represented by a distinct genotype. However by allowing a higher number of alleles to encode phenotypic information on the genotype, one can create a situation where a number of genotypes may represent the same phenotype. Through this process one can introduce the idea of redundancy or neutrality into the representation. This representation allows for adaptive mutation (hot spots) and silent mutation (cold spots). This combination enables the level of diversity to dynamically adjust during the search, and directs the search towards closely related neutral sets. Previous work has shown that introducing this type of representation can be beneficial; in this paper we show how this representation is useful at introducing and maintaining diversity. Here we compare the performance of the MGA against traditional diversifying techniques used in conjunction with a SGA over a fully deceptive changing landscape.en_IE
dc.formatapplication/pdfen_IE
dc.language.isoenen_IE
dc.publisherSciTePress Digital Libraryen_IE
dc.relation.ispartof8th International Conference on Evolutionary Computation Theory and Applications ECTA Porto, Portugalen
dc.subjectGenetic driften_IE
dc.subjectNeutralityen_IE
dc.subjectGenotypeen_IE
dc.subjectPhenotypeen_IE
dc.subjectGenetic algorithmsen_IE
dc.subjectNeutral theoryen_IE
dc.titleDiversifying techniques and neutrality in genetic algorithmsen_IE
dc.typeConference Paperen_IE
dc.date.updated2018-12-05T15:42:39Z
dc.identifier.doi10.5220/0006036201400147
dc.local.publishedsourcehttps://dx.doi.org/10.5220/0006036201400147en_IE
dc.description.peer-reviewedpeer-reviewed
dc.internal.rssid15480444
dc.local.contactSéamus Hill, Information Technology. 5232 Email: seamus.hill@nuigalway.ie
dc.local.copyrightcheckedYes
dc.local.versionACCEPTED
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