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:1.8010
- @InProceedings{ziegler03,
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author = "Jens Ziegler and Wolfgang Banzhaf",
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title = "Decreasing the Number of Evaluations in Evolutionary
Algorithms by using a Meta-Model of the Fitness
Function",
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booktitle = "Genetic Programming, Proceedings of EuroGP'2003",
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year = "2003",
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editor = "Conor Ryan and Terence Soule and Maarten Keijzer and
Edward Tsang and Riccardo Poli and Ernesto Costa",
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volume = "2610",
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series = "LNCS",
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pages = "264--275",
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address = "Essex",
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publisher_address = "Berlin",
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month = "14-16 " # apr,
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organisation = "EvoNet",
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publisher = "Springer-Verlag",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "3-540-00971-X",
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DOI = "doi:10.1007/3-540-36599-0_24",
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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.",
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notes = "EuroGP'2003 held in conjunction with EvoWorkshops
2003",
- }
Genetic Programming entries for
Jens Ziegler
Wolfgang Banzhaf
Citations