The Influence of Population Size on Geometric Semantic GP

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

@InProceedings{Castelli:2014:SMGP,

• author = "Mauro Castelli and Luca Manzoni and Sara Silva and Leonardo Vanneschi",
• title = "The Influence of Population Size on Geometric Semantic GP",
• booktitle = "Semantic Methods in Genetic Programming",
• year = "2014",
• editor = "Colin Johnson and Krzysztof Krawiec and Alberto Moraglio and Michael O'Neill",
• address = "Ljubljana, Slovenia",
• month = "13 " # sep,
• note = "Workshop at Parallel Problem Solving from Nature 2014 conference",
• keywords = "genetic algorithms, genetic programming",
• URL = "http://www.cs.put.poznan.pl/kkrawiec/smgp2014/uploads/Site/Castelli.pdf",
• size = "2 pages",
• abstract = "In this work we study the influence of the population size on the learning ability of Geometric Semantic Genetic Programming (GSGP) for the task of symbolic regression. The results show that having small populations results on a better training fitness with respect to the use of large populations after the same number of fitness evaluations. However, models obtained with large populations show a better performance on unseen data.",
• notes = "SMGP 2014 http://www.cs.put.poznan.pl/kkrawiec/smgp/?n=Site.SMGP2014",

}

Genetic Programming entries for Mauro Castelli Luca Manzoni Sara Silva Leonardo Vanneschi

Citations