Geometric Semantic Genetic Programming with Normalized and Standardized Random Programs

Bibliographic Details
Main Author: Bakurov, Illya
Publication Date: 2024
Other Authors: Muñoz Contreras, José Manuel, Castelli, Mauro, Rodrigues, Nuno Miguel Duarte, Silva, Sara, Trujillo, Leonardo, Vanneschi, Leonardo
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/163602
Summary: Bakurov, I., Muñoz Contreras, J. M., Castelli, M., Rodrigues, N., Silva, S., Trujillo, L., & Vanneschi, L. (2024). Geometric Semantic Genetic Programming with Normalized and Standardized Random Programs. Genetic Programming And Evolvable Machines, 25, 1-29. Article 6. https://doi.org/10.1007/s10710-024-09479-1 --- This work was partially supported by FCT, Portugal, through funding of research units MagIC/NOVA IMS (UIDB/04152/2020) and LASIGE (UIDB/00408/2020 and UIDP/00408/2020). This work also was supported by CONACYT (Mexico) Project CF-2023-I-724, TecNM (Mexico) Project 16788.23-P and Project 17756.23-P. José Manuel Muñoz Contreras was supported by CONACYT scholarship 771416; Nuno Rodrigues was supported by FCT PhD Grant 2021/05322/BD.
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spelling Geometric Semantic Genetic Programming with Normalized and Standardized Random ProgramsGeometric semantic mutationInternal covariate shiftSigmoid distribution biasModel simplificationSoftwareTheoretical Computer ScienceHardware and ArchitectureComputer Science ApplicationsBakurov, I., Muñoz Contreras, J. M., Castelli, M., Rodrigues, N., Silva, S., Trujillo, L., & Vanneschi, L. (2024). Geometric Semantic Genetic Programming with Normalized and Standardized Random Programs. Genetic Programming And Evolvable Machines, 25, 1-29. Article 6. https://doi.org/10.1007/s10710-024-09479-1 --- This work was partially supported by FCT, Portugal, through funding of research units MagIC/NOVA IMS (UIDB/04152/2020) and LASIGE (UIDB/00408/2020 and UIDP/00408/2020). This work also was supported by CONACYT (Mexico) Project CF-2023-I-724, TecNM (Mexico) Project 16788.23-P and Project 17756.23-P. José Manuel Muñoz Contreras was supported by CONACYT scholarship 771416; Nuno Rodrigues was supported by FCT PhD Grant 2021/05322/BD.Geometric semantic genetic programming (GSGP) represents one of the most promising developments in the area of evolutionary computation (EC) in the last decade. The results achieved by incorporating semantic awareness in the evolutionary process demonstrate the impact that geometric semantic operators have brought to the field of EC. An improvement to the geometric semantic mutation (GSM) operator is proposed, inspired by the results achieved by batch normalization in deep learning. While, in one of its most used versions, GSM relies on the use of the sigmoid function to constrain the semantics of two random programs responsible for perturbing the parent’s semantics, here a different approach is followed, which allows reducing the size of the resulting programs and overcoming the issues associated with the use of the sigmoid function, as commonly done in deep learning. The idea is to consider a single random program and use it to perturb the parent’s semantics only after standardization or normalization. The experimental results demonstrate the suitability of the proposed approach: despite its simplicity, the presented GSM variants outperform standard GSGP on the studied benchmarks, with a difference in terms of performance that is statistically significant. Furthermore, the individuals generated by the new GSM variants are easier to simplify, allowing us to create accurate but significantly smaller solutions.Information Management Research Center (MagIC) - NOVA Information Management SchoolNOVA Information Management School (NOVA IMS)RUNBakurov, IllyaMuñoz Contreras, José ManuelCastelli, MauroRodrigues, Nuno Miguel DuarteSilva, SaraTrujillo, LeonardoVanneschi, Leonardo2025-02-09T01:31:48Z2024-06-012024-06-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article29application/pdfhttp://hdl.handle.net/10362/163602eng1389-2576PURE: 79765150https://doi.org/10.1007/s10710-024-09479-1info: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:RCAAP2025-02-10T01:36:17Zoai:run.unl.pt:10362/163602Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:49:00.048784Repositórios 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 Geometric Semantic Genetic Programming with Normalized and Standardized Random Programs
title Geometric Semantic Genetic Programming with Normalized and Standardized Random Programs
spellingShingle Geometric Semantic Genetic Programming with Normalized and Standardized Random Programs
Bakurov, Illya
Geometric semantic mutation
Internal covariate shift
Sigmoid distribution bias
Model simplification
Software
Theoretical Computer Science
Hardware and Architecture
Computer Science Applications
title_short Geometric Semantic Genetic Programming with Normalized and Standardized Random Programs
title_full Geometric Semantic Genetic Programming with Normalized and Standardized Random Programs
title_fullStr Geometric Semantic Genetic Programming with Normalized and Standardized Random Programs
title_full_unstemmed Geometric Semantic Genetic Programming with Normalized and Standardized Random Programs
title_sort Geometric Semantic Genetic Programming with Normalized and Standardized Random Programs
author Bakurov, Illya
author_facet Bakurov, Illya
Muñoz Contreras, José Manuel
Castelli, Mauro
Rodrigues, Nuno Miguel Duarte
Silva, Sara
Trujillo, Leonardo
Vanneschi, Leonardo
author_role author
author2 Muñoz Contreras, José Manuel
Castelli, Mauro
Rodrigues, Nuno Miguel Duarte
Silva, Sara
Trujillo, Leonardo
Vanneschi, Leonardo
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Information Management Research Center (MagIC) - NOVA Information Management School
NOVA Information Management School (NOVA IMS)
RUN
dc.contributor.author.fl_str_mv Bakurov, Illya
Muñoz Contreras, José Manuel
Castelli, Mauro
Rodrigues, Nuno Miguel Duarte
Silva, Sara
Trujillo, Leonardo
Vanneschi, Leonardo
dc.subject.por.fl_str_mv Geometric semantic mutation
Internal covariate shift
Sigmoid distribution bias
Model simplification
Software
Theoretical Computer Science
Hardware and Architecture
Computer Science Applications
topic Geometric semantic mutation
Internal covariate shift
Sigmoid distribution bias
Model simplification
Software
Theoretical Computer Science
Hardware and Architecture
Computer Science Applications
description Bakurov, I., Muñoz Contreras, J. M., Castelli, M., Rodrigues, N., Silva, S., Trujillo, L., & Vanneschi, L. (2024). Geometric Semantic Genetic Programming with Normalized and Standardized Random Programs. Genetic Programming And Evolvable Machines, 25, 1-29. Article 6. https://doi.org/10.1007/s10710-024-09479-1 --- This work was partially supported by FCT, Portugal, through funding of research units MagIC/NOVA IMS (UIDB/04152/2020) and LASIGE (UIDB/00408/2020 and UIDP/00408/2020). This work also was supported by CONACYT (Mexico) Project CF-2023-I-724, TecNM (Mexico) Project 16788.23-P and Project 17756.23-P. José Manuel Muñoz Contreras was supported by CONACYT scholarship 771416; Nuno Rodrigues was supported by FCT PhD Grant 2021/05322/BD.
publishDate 2024
dc.date.none.fl_str_mv 2024-06-01
2024-06-01T00:00:00Z
2025-02-09T01:31:48Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/163602
url http://hdl.handle.net/10362/163602
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1389-2576
PURE: 79765150
https://doi.org/10.1007/s10710-024-09479-1
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 29
application/pdf
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
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