Evolving modules in Genetic Programming by subtree encapsulation
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{roberts:2001:EuroGP,
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author = "Simon C. Roberts and Daniel Howard and John R. Koza",
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title = "Evolving modules in Genetic Programming by subtree
encapsulation",
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booktitle = "Genetic Programming, Proceedings of EuroGP'2001",
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year = "2001",
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editor = "Julian F. Miller and Marco Tomassini and
Pier Luca Lanzi and Conor Ryan and Andrea G. B. Tettamanzi and
William B. Langdon",
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volume = "2038",
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series = "LNCS",
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pages = "160--175",
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address = "Lake Como, Italy",
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publisher_address = "Berlin",
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month = "18-20 " # apr,
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organisation = "EvoNET",
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publisher = "Springer-Verlag",
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keywords = "genetic algorithms, genetic programming,
Modularisation, Code Reuse, Subtree Encapsulation,
Image Processing",
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ISBN = "3-540-41899-7",
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DOI = "doi:10.1007/3-540-45355-5_13",
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size = "16 pages",
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abstract = "In tree-based genetic programming (GP), the most
frequent subtrees on later generations are likely to
constitute useful partial solutions. This paper
investigates the effect of encapsulating such subtrees
by representing them as atoms in the terminal set, so
that the subtree evaluations can be exploited as
terminal data. The encapsulation scheme is compared
against a second scheme which depends on random subtree
selection. Empirical results show that both schemes
improve upon standard GP.",
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notes = "EuroGP'2001, part of \cite{miller:2001:gp}",
- }
Genetic Programming entries for
Simon C Roberts
Daniel Howard
John Koza
Citations