Population Sizing for Genetic Programming based on Decision Making
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InCollection{sastry:2004:GPTP,
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author = "Kumara Sastry and Una-May O'Reilly and
David E. Goldberg",
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title = "Population Sizing for Genetic Programming based on
Decision Making",
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booktitle = "Genetic Programming Theory and Practice {II}",
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year = "2004",
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editor = "Una-May O'Reilly and Tina Yu and Rick L. Riolo and
Bill Worzel",
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chapter = "4",
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pages = "49--65",
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address = "Ann Arbor",
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month = "13-15 " # may,
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, population
sizing, facet wise modelling, scalability",
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ISBN = "0-387-23253-2",
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URL = "http://arxiv.org/abs/cs/0502020",
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DOI = "doi:10.1007/0-387-23254-0_4",
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abstract = "This paper derives a population sizing relationship
for genetic programming (GP). Following the
population-sizing derivation for genetic algorithms in
Goldberg, Deb, and Clark (1992), it considers building
block decision making as a key facet. The analysis
yields a GP-unique relationship because it has to
account for bloat and for the fact that GP solutions
often use subsolution multiple times. The
population-sizing relationship depends upon tree size,
solution complexity, problem difficulty and building
block expression probability. The relationship is used
to analyse and empirically investigate population
sizing for three model GP problems named ORDER, ON-OFF
and LOUD. These problems exhibit bloat to differing
extents and differ in whether their solutions require
the use of a building block multiple times.",
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notes = "part of \cite{oreilly:2004:GPTP2} IlliGAL Report No.
2004028",
- }
Genetic Programming entries for
Kumara Sastry
Una-May O'Reilly
David E Goldberg
Citations