Introducing Crossover in SLIM-GSGP

Detalhes bibliográficos
Autor(a) principal: Pietropolli, Gloria
Data de Publicação: 2025
Outros Autores: Farinati, Davide, Manzoni, Luca, Castelli, Mauro, Silva, Sara, Vanneschi, Leonardo
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10362/182851
Resumo: Pietropolli, G., Farinati, D., Manzoni, L., Castelli, M., Silva, S., & Vanneschi, L. (2025). Introducing Crossover in SLIM-GSGP. In B. Xue, L. Manzoni, & I. Bakurov (Eds.), Genetic Programming: 28th European Conference, EuroGP 2025, Held as Part of EvoStar 2025, Trieste, Italy, April 23–25, 2025, Proceedings (pp. 103-119). (Lecture Notes in Computer Science; Vol. 15609). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-031-89991-1_7 --- This work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project - UIDB/04152/2020 (DOI: 10.54499/UIDB/04152/2020) - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS),(https://doi.org/10.54499/UIDB/04152/2020) the project 2024.07277. IACDC, and the LASIGE Research Unit, ref. UID/000408/2025.
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spelling Introducing Crossover in SLIM-GSGPSLIMGeometric Semantic Genetic ProgrammingGeometric Semantic CrossoverInflate MutationDeflate MutationTheoretical Computer ScienceComputer Science(all)Pietropolli, G., Farinati, D., Manzoni, L., Castelli, M., Silva, S., & Vanneschi, L. (2025). Introducing Crossover in SLIM-GSGP. In B. Xue, L. Manzoni, & I. Bakurov (Eds.), Genetic Programming: 28th European Conference, EuroGP 2025, Held as Part of EvoStar 2025, Trieste, Italy, April 23–25, 2025, Proceedings (pp. 103-119). (Lecture Notes in Computer Science; Vol. 15609). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-031-89991-1_7 --- This work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project - UIDB/04152/2020 (DOI: 10.54499/UIDB/04152/2020) - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS),(https://doi.org/10.54499/UIDB/04152/2020) the project 2024.07277. IACDC, and the LASIGE Research Unit, ref. UID/000408/2025.The Semantic Learning algorithm based on Inflate and deflate Mutations (SLIM-GSGP, or simply SLIM) is a variant of Geometric Semantic Genetic Programming (GSGP) designed to generate compact and interpretable models while maintaining the beneficial characteristic of GSGP of inducing an error surface without local optima. To date, no crossover operator has been defined for SLIM and the existing SLIM framework relies solely on two mutation operators: inflate and deflate mutation. This paper introduces two novel crossover operators for SLIM: Swap Crossover (XOSw) and Donor Crossover (XODn). These crossovers capitalize on SLIM’s linked-list representation to facilitate genetic exchange while controlling program size. Experimental results on five symbolic regression problems demonstrate that the new crossover operators often improve fitness and reduce model size when compared to standard SLIM and to GSGP. Our findings establish these operators as solid improvements of traditional GSGP crossover.Springer Nature Switzerland AGNOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNPietropolli, GloriaFarinati, DavideManzoni, LucaCastelli, MauroSilva, SaraVanneschi, Leonardo2025-04-222026-04-18T00:00:00Z2025-04-22T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersion17application/pdfhttp://hdl.handle.net/10362/182851eng978-3-031-89990-40302-9743PURE: 115880472https://doi.org/10.1007/978-3-031-89991-1_7info:eu-repo/semantics/embargoedAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-05-19T01:40:13Zoai:run.unl.pt:10362/182851Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T07:14:12.754814Repositórios 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 Introducing Crossover in SLIM-GSGP
title Introducing Crossover in SLIM-GSGP
spellingShingle Introducing Crossover in SLIM-GSGP
Pietropolli, Gloria
SLIM
Geometric Semantic Genetic Programming
Geometric Semantic Crossover
Inflate Mutation
Deflate Mutation
Theoretical Computer Science
Computer Science(all)
title_short Introducing Crossover in SLIM-GSGP
title_full Introducing Crossover in SLIM-GSGP
title_fullStr Introducing Crossover in SLIM-GSGP
title_full_unstemmed Introducing Crossover in SLIM-GSGP
title_sort Introducing Crossover in SLIM-GSGP
author Pietropolli, Gloria
author_facet Pietropolli, Gloria
Farinati, Davide
Manzoni, Luca
Castelli, Mauro
Silva, Sara
Vanneschi, Leonardo
author_role author
author2 Farinati, Davide
Manzoni, Luca
Castelli, Mauro
Silva, Sara
Vanneschi, Leonardo
author2_role author
author
author
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 Pietropolli, Gloria
Farinati, Davide
Manzoni, Luca
Castelli, Mauro
Silva, Sara
Vanneschi, Leonardo
dc.subject.por.fl_str_mv SLIM
Geometric Semantic Genetic Programming
Geometric Semantic Crossover
Inflate Mutation
Deflate Mutation
Theoretical Computer Science
Computer Science(all)
topic SLIM
Geometric Semantic Genetic Programming
Geometric Semantic Crossover
Inflate Mutation
Deflate Mutation
Theoretical Computer Science
Computer Science(all)
description Pietropolli, G., Farinati, D., Manzoni, L., Castelli, M., Silva, S., & Vanneschi, L. (2025). Introducing Crossover in SLIM-GSGP. In B. Xue, L. Manzoni, & I. Bakurov (Eds.), Genetic Programming: 28th European Conference, EuroGP 2025, Held as Part of EvoStar 2025, Trieste, Italy, April 23–25, 2025, Proceedings (pp. 103-119). (Lecture Notes in Computer Science; Vol. 15609). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-031-89991-1_7 --- This work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project - UIDB/04152/2020 (DOI: 10.54499/UIDB/04152/2020) - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS),(https://doi.org/10.54499/UIDB/04152/2020) the project 2024.07277. IACDC, and the LASIGE Research Unit, ref. UID/000408/2025.
publishDate 2025
dc.date.none.fl_str_mv 2025-04-22
2025-04-22T00:00:00Z
2026-04-18T00:00:00Z
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