Towards Discrete Phenotypic Recombination in Cartesian Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7650

@InProceedings{DBLP:conf/ppsn/Kalkreuth22,

• author = "Roman Kalkreuth",
• title = "Towards Discrete Phenotypic Recombination in Cartesian Genetic Programming",
• booktitle = "Parallel Problem Solving from Nature - PPSN XVII - 17th International Conference, PPSN 2022, Proceedings, Part II",
• year = "2022",
• editor = "Guenter Rudolph and Anna V. Kononova and Hernan E. Aguirre and Pascal Kerschke and Gabriela Ochoa and Tea Tusar",
• volume = "13399",
• series = "Lecture Notes in Computer Science",
• pages = "63--77",
• address = "Dortmund, Germany",
• month = sep # " 10-14",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, Cartesian Genetic Programming, Crossover, Phenotypic variation",
• timestamp = "Tue, 16 Aug 2022 16:15:42 +0200",
• biburl = "https://dblp.org/rec/conf/ppsn/Kalkreuth22.bib",
• bibsource = "dblp computer science bibliography, https://dblp.org",
• isbn13 = "978-3-031-14720-3",
• DOI = "doi:10.1007/978-3-031-14721-0_5",
• abstract = "we propose a phenotypic variation method for discrete recombination in CGP. We compare our method to the traditional mutation-only CGP approach on a set of well-known symbolic regression problems. The initial results presented in this work demonstrate that the use of our proposed discrete recombination method performs significantly better than the traditional mutation-only approach.",
• notes = "PPSN2022",

}

Genetic Programming entries for Roman Tobias Kalkreuth

Citations