A multiple expression alignment framework for genetic programming

Detalhes bibliográficos
Autor(a) principal: Vanneschi, Leonardo
Data de Publicação: 2018
Outros Autores: Scott, Kristen, Castelli, Mauro
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10362/146338
Resumo: Vanneschi, L., Scott, K., & Castelli, M. (2018). A multiple expression alignment framework for genetic programming. In M. Castelli, L. Sekanina, M. Zhang, S. Cagnoni, & P. García-Sánchez (Eds.), Genetic Programming: 21st European Conference, EuroGP 2018, Proceedings, pp. 166-183. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10781 LNCS). Springer Verlag. DOI: 10.1007/978-3-319-77553-1_11
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spelling A multiple expression alignment framework for genetic programmingTheoretical Computer ScienceComputer Science(all)Vanneschi, L., Scott, K., & Castelli, M. (2018). A multiple expression alignment framework for genetic programming. In M. Castelli, L. Sekanina, M. Zhang, S. Cagnoni, & P. García-Sánchez (Eds.), Genetic Programming: 21st European Conference, EuroGP 2018, Proceedings, pp. 166-183. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10781 LNCS). Springer Verlag. DOI: 10.1007/978-3-319-77553-1_11Alignment 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. As a consequence, genetic programming methods, aimed at searching for optimally aligned, or optimally coplanar, individuals were introduced. In this paper, we critically discuss those methods, analyzing their major limitations and we propose new genetic programming systems aimed at overcoming those limitations. The presented experimental results, conducted on four 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.Springer VerlagNOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNVanneschi, LeonardoScott, KristenCastelli, Mauro2022-12-16T22:18:16Z2018-01-012018-01-01T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersion18application/pdfhttp://hdl.handle.net/10362/146338eng97833197755240302-9743PURE: 3938611https://doi.org/10.1007/978-3-319-77553-1_11info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-07-22T01:36:39Zoai:run.unl.pt:10362/146338Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:38:08.362604Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
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
Vanneschi, Leonardo
Theoretical Computer Science
Computer Science(all)
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 Vanneschi, Leonardo
author_facet Vanneschi, Leonardo
Scott, Kristen
Castelli, Mauro
author_role author
author2 Scott, Kristen
Castelli, Mauro
author2_role author
author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Vanneschi, Leonardo
Scott, Kristen
Castelli, Mauro
dc.subject.por.fl_str_mv Theoretical Computer Science
Computer Science(all)
topic Theoretical Computer Science
Computer Science(all)
description Vanneschi, L., Scott, K., & Castelli, M. (2018). A multiple expression alignment framework for genetic programming. In M. Castelli, L. Sekanina, M. Zhang, S. Cagnoni, & P. García-Sánchez (Eds.), Genetic Programming: 21st European Conference, EuroGP 2018, Proceedings, pp. 166-183. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10781 LNCS). Springer Verlag. DOI: 10.1007/978-3-319-77553-1_11
publishDate 2018
dc.date.none.fl_str_mv 2018-01-01
2018-01-01T00:00:00Z
2022-12-16T22:18:16Z
dc.type.driver.fl_str_mv conference object
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/146338
url http://hdl.handle.net/10362/146338
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 9783319775524
0302-9743
PURE: 3938611
https://doi.org/10.1007/978-3-319-77553-1_11
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 18
application/pdf
dc.publisher.none.fl_str_mv Springer Verlag
publisher.none.fl_str_mv Springer Verlag
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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