Directing Crossover for Reduction of Bloat in GP
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{terrio:dcfr,
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author = "M. Terrio and M. I. Heywood",
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title = "Directing Crossover for Reduction of Bloat in GP",
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booktitle = "IEEE CCECE 2003: IEEE Canadian Conference on
Electrical and Computer Engineering",
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year = "2002",
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editor = "W. Kinsner and A. Seback and K. Ferens",
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pages = "1111--1115",
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month = "12-15 " # may,
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organisation = "IEEE Canada",
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming, Code Bloat",
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ISBN = "0-7803-7515-7",
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URL = "http://users.cs.dal.ca/~mheywood/X-files/Publications/CCECE-272.pdf",
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URL = "http://citeseer.ist.psu.edu/758918.html",
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abstract = "A method is proposed to reduce the amount of inviable
code (or bloat) produced in individuals while searching
for a parsimonious solution under tree structured
genetic programming. Known as directed crossover, this
process involves the identification of highly fit nodes
to use as crossover points during operator application.
Three test problems, including medical data
classification, are used to assess the performance of
directed crossover when applied at various thresholds.
Results, collected over 1260 independent runs, identify
conditions under which directed crossover reduces code
bloat.",
- }
Genetic Programming entries for
M David Terrio
Malcolm Heywood
Citations