Towards Phenotypic Duplication and Inversion in Cartesian Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8237

@InProceedings{DBLP:conf/ijcci/Kalkreuth22,

• author = "Roman Kalkreuth",
• title = "Towards Phenotypic Duplication and Inversion in Cartesian Genetic Programming",
• booktitle = "Proceedings of the 14th International Joint Conference on Computational Intelligence, IJCCI 2022",
• editor = "Thomas B{\"{a}}ck and Bas {van Stein} and Christian Wagner and Jonathan M. Garibaldi and H. K. Lam and Marie Cottrell and Faiyaz Doctor and Joaquim Filipe and Kevin Warwick and Janusz Kacprzyk",
• pages = "50--61",
• publisher = "Scitepress",
• year = "2022",
• address = "Valletta, Malta",
• month = oct # " 24-26",
• keywords = "genetic algorithms, genetic programming, Cartesian Genetic Programming, Mutation, Duplication, Inversion, Boolean Function Learning",
• isbn13 = "978-989-758-611-8",
• ISSN = "2184-3236",
• timestamp = "Mon, 14 Nov 2022 00:00:00 +0100",
• biburl = "https://dblp.org/rec/conf/ijcci/Kalkreuth22.bib",
• bibsource = "dblp computer science bibliography, https://dblp.org",
• URL = "https://www.scitepress.org/Papers/2022/115510/115510.pdf",
• DOI = "doi:10.5220/0011551000003332",
• size = "12 pages",
• abstract = "The search performance of Cartesian Genetic Programming (CGP) relies to a large extent on the sole use of genotypic point mutation in combination with extremely large redundant genotypes. Over the last years, steps have been taken to extend CGP variation mechanisms by the introduction of advanced methods for recombination and mutation. One branch of these contributions addresses phenotypic variation in CGP. Besides demonstrating the effectiveness of various phenotypic search operators, corresponding analytical experiments backed evidence that phenotypic variation is another approach for achieving effective evolutionary-driven search in CGP. However, recent comparative studies have demonstrated the limitations of phenotypic recombination in Boolean function learning and highlighted the effectiveness of the mutation-only approach. Especially the use of the 1+lambda selection strategy with neutral genetic drift has been found superior to recombination-based approaches in this problem domain. Therefore we further explore phenotypic mutation in CGP by the introduction and evaluation of two phenotypic mutation operators that are inspired by chromosomal rearrangement. Our initial findings show that our proposed methods can significantly improve the search performance of CGP on various single- and multiple-output Boolean function benchmarks by reducing the number of fitness evaluations needed to find the ideal solution",

}

Genetic Programming entries for Roman Tobias Kalkreuth

Citations