A multiple expression alignment framework for genetic programming

Detalhes bibliográficos
Autor(a) principal: Scott, Kristen Marie
Data de Publicação: 2018
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/40749
Resumo: Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
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spelling A multiple expression alignment framework for genetic programmingGenetic ProgrammingGeometric Semantic Genetic ProgrammingError Space Genetic ProgrammingDissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced AnalyticsAlignment in the error space is a recent idea to exploit semantic awareness in genetic programming. In a previous contribution, the concepts of optimally aligned and optimally coplanar individuals were introduced, and it was shown that given optimally aligned, or optimally coplanar, individuals, it is possible to construct a globally optimal solution analytically. Consequently, genetic programming methods, aimed at searching for optimally aligned, or optimally coplanar, individuals were introduced. This paper critically discusses those methods, analyzing their major limitations and introduces a new genetic programming system aimed at overcoming those limitations. The presented experimental results, conducted on five real-life symbolic regression problems, show that the proposed algorithms’ outperform not only the existing methods based on the concept of alignment in the error space, but also geometric semantic genetic programming and standard genetic programming.Vanneschi, LeonardoCastelli, MauroRUNScott, Kristen Marie2018-07-03T17:23:52Z2018-07-032018-07-03T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/40749TID:201948672enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:22:06Zoai:run.unl.pt:10362/40749Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:31:16.656443Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv A multiple expression alignment framework for genetic programming
title A multiple expression alignment framework for genetic programming
spellingShingle A multiple expression alignment framework for genetic programming
Scott, Kristen Marie
Genetic Programming
Geometric Semantic Genetic Programming
Error Space Genetic Programming
title_short A multiple expression alignment framework for genetic programming
title_full A multiple expression alignment framework for genetic programming
title_fullStr A multiple expression alignment framework for genetic programming
title_full_unstemmed A multiple expression alignment framework for genetic programming
title_sort A multiple expression alignment framework for genetic programming
author Scott, Kristen Marie
author_facet Scott, Kristen Marie
author_role author
dc.contributor.none.fl_str_mv Vanneschi, Leonardo
Castelli, Mauro
RUN
dc.contributor.author.fl_str_mv Scott, Kristen Marie
dc.subject.por.fl_str_mv Genetic Programming
Geometric Semantic Genetic Programming
Error Space Genetic Programming
topic Genetic Programming
Geometric Semantic Genetic Programming
Error Space Genetic Programming
description Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
publishDate 2018
dc.date.none.fl_str_mv 2018-07-03T17:23:52Z
2018-07-03
2018-07-03T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/40749
TID:201948672
url http://hdl.handle.net/10362/40749
identifier_str_mv TID:201948672
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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