Extension of Genetic Programming with Multiple Trees for Agent Learning
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{journals/jcp/ItoTI16,
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author = "Takashi Ito and Kenichi Takahashi and
Michimasa Inaba",
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title = "Extension of Genetic Programming with Multiple Trees
for Agent Learning",
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journal = "Journal of Computers",
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year = "2016",
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number = "4",
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volume = "11",
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pages = "329--340",
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keywords = "genetic algorithms, genetic programming, Autonomous
agent, conditional probability, island model",
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bibdate = "2016-06-09",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/journals/jcp/jcp11.html#ItoTI16",
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ISSN = "1796-203X",
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URL = "http://www.jcomputers.us/index.php?m=content&c=index&a=show&catid=179&id=2649",
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URL = "http://www.jcomputers.us/vol11/jcp1104-07.pdf",
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DOI = "doi:10.17706/jcp.11.4.329-340",
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size = "12 pages",
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abstract = "This paper proposes an extension of genetic
programming (GP) with multiple trees. In order to
improve the performance, GP with control node (GPCN)
and its three kinds of modification have been proposed.
In GPCN, an individual consists of several trees which
have the number P of executions. In previous work, the
two kinds of modification, the conditional probability
and the cross-cultural island model are employed. This
paper proposes two methods: the new island model that
combines the conditional probability with two islands
in the cross-cultural island model and a method
exchanges multiple trees in an individual in a suitable
order. Experiments are conducted to show the
performance in the garbage collection problem and the
Santa Fe Trail problem.",
- }
Genetic Programming entries for
Takashi Ito
Ken-ichi Takahashi
Michimasa Inaba
Citations