Extending local search in geometric semantic genetic programming

Mauro Castelli, Luca Manzoni, Luca Mariot, Martina Saletta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

In this paper we continue the investigation of the effect of local search in geometric semantic genetic programming (GSGP), with the introduction of a new general local search operator that can be easily customized. We show that it is able to obtain results on par with the current best-performing GSGP with local search and, in most cases, better than standard GSGP.

Original languageEnglish
Title of host publicationProgress in Artificial Intelligence
Subtitle of host publication19th EPIA Conference on Artificial Intelligence, EPIA 2019, Proceedings
EditorsPaulo Moura Oliveira, Paulo Novais, Luís Paulo Reis
PublisherSpringer Verlag
Pages775-787
Number of pages13
ISBN (Electronic)978-3-030-30241-2
ISBN (Print)978-3-030-30240-5
DOIs
Publication statusPublished - 1 Sep 2019
Event19th EPIA Conference on Artificial Intelligence, EPIA 2019 - Vila Real, Portugal
Duration: 3 Sep 20196 Sep 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11804 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th EPIA Conference on Artificial Intelligence, EPIA 2019
CountryPortugal
CityVila Real
Period3/09/196/09/19

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  • Cite this

    Castelli, M., Manzoni, L., Mariot, L., & Saletta, M. (2019). Extending local search in geometric semantic genetic programming. In P. Moura Oliveira, P. Novais, & L. P. Reis (Eds.), Progress in Artificial Intelligence : 19th EPIA Conference on Artificial Intelligence, EPIA 2019, Proceedings (pp. 775-787). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11804 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-030-30241-2_64