Problem Difficulty and Code Growth in Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @Article{gustafson:2004:GPEM,
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author = "Steven Gustafson and Aniko Ekart and Edmund Burke and
Graham Kendall",
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title = "Problem Difficulty and Code Growth in Genetic
Programming",
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journal = "Genetic Programming and Evolvable Machines",
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year = "2004",
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volume = "5",
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number = "3",
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pages = "271--290",
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month = sep,
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keywords = "genetic algorithms, genetic programming, population
diversity, code growth, problem difficulty",
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ISSN = "1389-2576",
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URL = "http://www.gustafsonresearch.com/research/publications/gustafson-gpem2004.pdf",
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DOI = "doi:10.1023/B:GENP.0000030194.98244.e3",
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size = "20 pages",
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abstract = "the relationship between code growth and problem
difficulty in genetic programming. The symbolic
regression problem domain is used to investigate this
relationship using two different types of increased
instance difficulty. Results are supported by a
simplified model of genetic programming and show that
increased difficulty induces higher selection pressure
and less genetic diversity, which both contribute
toward an increased rate of code growth.",
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notes = "Article ID: 5272970",
- }
Genetic Programming entries for
Steven M Gustafson
Aniko Ekart
Edmund Burke
Graham Kendall
Citations