A case study where biology inspired a solution to a computer science problem
Created by W.Langdon from
gp-bibliography.bib Revision:1.8194
- @InProceedings{koza:1996:biscsp,
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author = "John R. Koza and David Andre",
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title = "A case study where biology inspired a solution to a
computer science problem",
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booktitle = "Pacific Symposium on Biocomputing '96",
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year = "1996",
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editor = "Lawrence Hunter and Teri E. Klein",
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pages = "500--511",
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publisher_address = "Singapore",
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publisher = "World Scientific",
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keywords = "genetic algorithms, genetic programming",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.368.6585",
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URL = "http://www.genetic-programming.com/jkpdf/psb1996.pdf",
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abstract = "This paper describes how the biological theory of gene
duplication described in Susumu Ohno's provocative
book, Evolution by Means of Gene Duplication, was
brought to bear on a vexatious problem from the domain
of automated machine learning, namely the problem of
architecture discovery. An automatic programming system
should require that the user make as few
problem-specific decisions as possible concerning the
size, shape, and character of the ultimate solution to
the problem. Six new architecture-altering operations
enable genetic programming to automatically discover an
appropriate architecture for solving the problem
concurrently with its efforts to solve the problem.
These architecture-altering operations were motivated
by the way that new biological structures, functions,
and behaviors arise in nature using gene duplication.
Genetic programming with the new architecture-altering
operations was then applied to the transmembrane
protein segment identification problem. The
out-of-sample error rate for the best
genetically-evolved program achieved was slightly
better than that of previously-reported human-written
algorithms for this problem.",
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notes = "PSB 96",
- }
Genetic Programming entries for
John Koza
David Andre
Citations