Controlling Individuals Growth in Semantic Genetic Programming through Elitist Replacement

In 2012, Moraglio and coauthors introduced new genetic operators for Genetic Programming, called geometric semantic genetic operators. They have the very interesting advantage of inducing a unimodal error surface for any supervised learning problem. At the same time, they have the important drawback...

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Detalles Bibliográficos
Autores principales: Castelli, Mauro, Vanneschi, Leonardo, Popovič, Aleš
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4707023/
https://www.ncbi.nlm.nih.gov/pubmed/27057158
http://dx.doi.org/10.1155/2016/8326760

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4707023/
https://www.ncbi.nlm.nih.gov/pubmed/27057158
http://dx.doi.org/10.1155/2016/8326760

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