Empirical Comparison of Evolutionary Representations of the Inverse Problem for Iterated Function Systems
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{eurogp07:sarafopoulos,
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author = "Anargyros Sarafopoulos and Bernard Buxton",
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title = "Empirical Comparison of Evolutionary Representations
of the Inverse Problem for Iterated Function Systems",
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editor = "Marc Ebner and Michael O'Neill and Anik\'o Ek\'art and
Leonardo Vanneschi and Anna Isabel Esparcia-Alc\'azar",
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booktitle = "Proceedings of the 10th European Conference on Genetic
Programming",
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publisher = "Springer",
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series = "Lecture Notes in Computer Science",
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volume = "4445",
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year = "2007",
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address = "Valencia, Spain",
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month = "11-13 " # apr,
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pages = "68--77",
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organisation = "EvoStar",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "3-540-71602-5",
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isbn13 = "978-3-540-71602-0",
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DOI = "doi:10.1007/978-3-540-71605-1_7",
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size = "10 pages",
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abstract = "In this paper we present an empirical comparison
between evolutionary representations for the resolution
of the inverse problem for iterated function systems
(IFS). We introduce a class of problem instances that
can be used for the comparison of the inverse IFS
problem as well as a novel technique that aids
exploratory analysis of experiment data. Our comparison
suggests that representations that exploit problem
specific information, apart from quality/fitness
feedback, perform better for the resolution of the
inverse problem for IFS.",
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notes = "Part of \cite{ebner:2007:GP} EuroGP'2007 held in
conjunction with EvoCOP2007, EvoBIO2007 and
EvoWorkshops2007",
- }
Genetic Programming entries for
Anargyros Sarafopoulos
Bernard Buxton
Citations