Quadratic Bloat in Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{langdon:2000:quad,
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author = "W. B. Langdon",
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title = "Quadratic Bloat in Genetic Programming",
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pages = "451--458",
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year = "2000",
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publisher = "Morgan Kaufmann",
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booktitle = "Proceedings of the Genetic and Evolutionary
Computation Conference (GECCO-2000)",
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editor = "Darrell Whitley and David Goldberg and
Erick Cantu-Paz and Lee Spector and Ian Parmee and Hans-Georg Beyer",
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address = "Las Vegas, Nevada, USA",
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publisher_address = "San Francisco, CA 94104, USA",
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month = "10-12 " # jul,
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keywords = "genetic algorithms, genetic programming, bloat,
introns, ineffective code, evolution of shape,
subquadratic length growth, linear depth growth, binary
tree search spaces",
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ISBN = "1-55860-708-0",
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URL = "http://gpbib.cs.ucl.ac.uk/gecco2000/GA069.pdf",
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URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/WBL.gecco2000.quad.ps.gz",
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URL = "http://gpbib.cs.ucl.ac.uk/gecco2000/GA069.ps",
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URL = "http://citeseer.ist.psu.edu/316810.html",
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URL = "http://dl.acm.org/citation.cfm?id=2933718.2933802",
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acmid = "2933802",
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size = "8 pages",
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abstract = "In earlier work we predicted program size would grow
in the limit at a quadratic rate and up to fifty
generations we measured bloat
O(generations**(1.2-1.5)). On two simple benchmarks we
test the prediction of bloat O(generations**2.0) up to
generation 600. In continuous problems the limit of
quadratic growth is reached but convergence in the
discrete case limits growth in size. Measurements
indicate subtree crossover ceases to be disruptive with
large programs (1,000,000) and the population
effectively converges (even though variety is near
unity). Depending upon implementation, we predict run
time O(number of generations**(2.0-3.0)) and memory
O(number of generations**(1.0-2.0)).",
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notes = "A joint meeting of the ninth International Conference
on Genetic Algorithms (ICGA-2000) and the fifth Annual
Genetic Programming Conference (GP-2000) Part of
\cite{whitley:2000:GECCO}",
- }
Genetic Programming entries for
William B Langdon
Citations