Semantic genetic operators based on a selection mechanism tailored for the root function

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Sanchez:2017:ROPEC,

• author = "Claudia N. Sanchez and Mario Graff",
• booktitle = "2017 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)",
• title = "Semantic genetic operators based on a selection mechanism tailored for the root function",
• year = "2017",
• month = "8-10 " # nov,
• address = "Ixtapa, Mexico",
• keywords = "genetic algorithms, genetic programming, Semantic Genetic Programming, Desired Semantics, Tournament Selection, EvoDAG, Python",
• DOI = "doi:10.1109/ROPEC.2017.8261638",
• isbn13 = "978-1-5386-0820-3",
• size = "6 pages",
• abstract = "Genetic Programming (GP) is an evolutionary algorithm that has received a lot of attention because it has been successfully applied to solving hard real problems. Furthermore, it has been shown that the use of semantic operators can improve GP performance in supervised learning problems. for parents selection, target semantics and function properties are used. We propose three new selection techniques: tournament selection based on desired semantics, tournament selection based on the orthogonality and tournament selection for one argument functions. To prove the performance of our proposal, we test our implementation with different classification problems.",
• notes = "Also known as \cite{8261638}

  Gunnar Raetsch Benchmark Datasets

  https://2017.ropec.org/technical_program/ XIX ROPEC 132

  INFOTEC Centro de Investigaci on e Innovacion en Tecnologias de la Informaci on y Comunicaci on Aguascalientes, Mexico",

}

Genetic Programming entries for Claudia Nallely Sanchez Gomez Mario Graff Guerrero

Citations