Fitness Distance Correlation in Structural Mutation Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{vanneschi03,
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author = "Leonardo Vanneschi and Marco Tomassini and
Philippe Collard and Manuel Clergue",
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title = "Fitness Distance Correlation in Structural Mutation
Genetic Programming",
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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 = "455--464",
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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: Poster",
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ISBN = "3-540-00971-X",
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DOI = "doi:10.1007/3-540-36599-0_43",
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abstract = "A new kind of mutation for genetic programming based
on the structural distance operators for trees is
presented in this paper. We firstly describe a new
genetic programming process based on these operators
(we call it structural mutation genetic programming).
Then we use structural distance to calculate the
fitness distance correlation coefficient and we show
that this coefficient is a reasonable measure to
express problem difficulty for structural mutation
genetic programming for the considered set of problems,
i.e. unimodal trap functions, royal trees and MAX
problem.",
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notes = "EuroGP'2003 held in conjunction with EvoWorkshops
2003",
- }
Genetic Programming entries for
Leonardo Vanneschi
Marco Tomassini
Philippe Collard
Manuel Clergue
Citations