Decreasing the Number of Evaluations in Evolutionary Algorithms by using a Meta-Model of the Fitness Function

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{ziegler03,

• author = "Jens Ziegler and Wolfgang Banzhaf",
• title = "Decreasing the Number of Evaluations in Evolutionary Algorithms by using a Meta-Model of the Fitness Function",
• booktitle = "Genetic Programming, Proceedings of EuroGP'2003",
• year = "2003",
• editor = "Conor Ryan and Terence Soule and Maarten Keijzer and Edward Tsang and Riccardo Poli and Ernesto Costa",
• volume = "2610",
• series = "LNCS",
• pages = "264--275",
• address = "Essex",
• publisher_address = "Berlin",
• month = "14-16 " # apr,
• organisation = "EvoNet",
• publisher = "Springer-Verlag",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "3-540-00971-X",
• DOI = "doi:10.1007/3-540-36599-0_24",
• abstract = "In this paper a method is presented that decreases the necessary number of evaluations in Evolutionary Algorithms. A classifier with confidence information is evolved to replace time consuming evaluations during tournament selection. Experimental analysis of a mathematical example and the application of the method to the problem of evolving walking patterns for quadruped robots show the potential of the presented approach.",
• notes = "EuroGP'2003 held in conjunction with EvoWorkshops 2003",

}

Genetic Programming entries for Jens Ziegler Wolfgang Banzhaf

Citations