Characterizing Diversity in Genetic Programming

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

@InProceedings{eurogp06:WynsDeBruyneBoullart,

• author = "Bart Wyns and Peter {De Bruyne} and Luc Boullart",
• title = "Characterizing Diversity in Genetic Programming",
• editor = "Pierre Collet and Marco Tomassini and Marc Ebner and Steven Gustafson and Anik\'o Ek\'art",
• booktitle = "Proceedings of the 9th European Conference on Genetic Programming",
• publisher = "Springer",
• series = "Lecture Notes in Computer Science",
• volume = "3905",
• year = "2006",
• address = "Budapest, Hungary",
• month = "10 - 12 " # apr,
• organisation = "EvoNet",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "3-540-33143-3",
• pages = "250--259",
• DOI = "doi:10.1007/11729976_22",
• bibsource = "DBLP, http://dblp.uni-trier.de",
• abstract = "In many evolutionary algorithms candidate solutions run the risk of getting stuck in local optima after a few generations of optimisation. In this paper two improved approaches to measure population diversity are proposed and validated using two traditional test problems in genetic programming literature. Code growth gave rise to improve pseudo-isomorph measures by eliminating non-functional code using an expression simplifier. Also, Rosca's entropy to measure behavioural diversity is updated to cope with problems producing a more continuous fitness value. Results show a relevant improvement with regard to the original diversity measures.",
• notes = "Part of \cite{collet:2006:GP} EuroGP'2006 held in conjunction with EvoCOP2006 and EvoWorkshops2006",

}

Genetic Programming entries for Bart Wyns Peter De Bruyne Luc Boullart

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