Redundancies in linear GP, canonical transformation, and its exploitation: a demonstration on image feature synthesis
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @Article{Watchareeruetai:2011:GPEM,
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author = "Ukrit Watchareeruetai and Yoshinori Takeuchi and
Tetsuya Matsumoto and Hiroaki Kudo and Noboru Ohnishi",
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title = "Redundancies in linear GP, canonical transformation,
and its exploitation: a demonstration on image feature
synthesis",
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journal = "Genetic Programming and Evolvable Machines",
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year = "2011",
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volume = "12",
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number = "1",
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pages = "49--77",
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month = mar,
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keywords = "genetic algorithms, genetic programming, Linear
genetic programming, Redundant representation,
Canonical form, Canonical transformation, Feature
extraction",
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ISSN = "1389-2576",
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DOI = "doi:10.1007/s10710-010-9118-x",
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abstract = "This paper concerns redundancies in representation of
linear genetic programming (GP). We identify the causes
of redundancies in linear GP and propose a canonical
transformation that converts original linear
representations into a canonical form in which
structural redundancies are removed. In canonical form,
we can easily verify whether two representations
represent an identical program. We then discuss
exploitation of the proposed canonical transformation,
and demonstrate a way to improve search performance of
linear GP by avoiding redundant individuals.
Experiments were conducted with an image feature
synthesis problem. Firstly, we have verified that there
are really a lot of redundancies in conventional linear
GP. We then investigate the effect of avoiding
redundant individuals. The results yield that linear GP
with avoidance of redundant individuals obviously
outperforms conventional linear GP.",
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affiliation = "Nagoya University Department of Media Science,
Graduate School of Information Science Furo-cho,
Chikusa-ku Nagoya 464-8603 Japan",
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notes = "replaces \cite{Watchareeruetai:2008:cec}",
- }
Genetic Programming entries for
Ukrit WatchAreeruetai
Yoshinori Takeuchi
Tetsuya Matsumoto
Hiroaki Kudo
Noboru Ohnishi
Citations