The Dynamics of Biased Inductive Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{nikolaev:1998:dbiGP,
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author = "Nikolay I. Nikolaev and Vanio Slavov",
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title = "The Dynamics of Biased Inductive Genetic Programming",
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booktitle = "Genetic Programming 1998: Proceedings of the Third
Annual Conference",
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year = "1998",
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editor = "John R. Koza and Wolfgang Banzhaf and
Kumar Chellapilla and Kalyanmoy Deb and Marco Dorigo and
David B. Fogel and Max H. Garzon and
David E. Goldberg and Hitoshi Iba and Rick Riolo",
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pages = "260--268",
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address = "University of Wisconsin, Madison, Wisconsin, USA",
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publisher_address = "San Francisco, CA, USA",
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month = "22-25 " # jul,
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publisher = "Morgan Kaufmann",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "1-55860-548-7",
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broken = "http://homepages.gold.ac.uk/nikolaev/gp98.ps.gz",
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URL = "http://citeseer.ist.psu.edu/cache/papers/cs/26570/http:zSzzSzwww.niss.gov.uazSzCenterzSzarticleszSzpaperszSzeurogp98.pdf/nikolaev98concepts.pdf",
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URL = "http://citeseer.ist.psu.edu/cache/papers/cs/23849/http:zSzzSzhomepages.gold.ac.ukzSznikolaevzSzgp98.pdf/the-dynamics-of-biased.pdf",
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URL = "http://citeseer.ist.psu.edu/468314.html",
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size = "8 pages",
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abstract = "We propose integrated navigation and fitness biases as
efficiency regulators for inductive Genetic
Programming. Evolutionary search is easy on smooth
landscapes created with size-biased stochastic
complexity fitness functions. In order to achieve
continuous guidance to unvisited landscape areas, these
functions require mutation and crossover applications,
biased by the size of the genetic programs. The
evolutionary dynamics of this approach is investigated
with population diameter, structural entropy and energy
estimates. These estimates provide valuable information
for the evolutionary algorithm behavior, with which we
may explain and predict its search efficiency. We
demonstrate empiricaly that the use of integrated
biases contributes to achieve efficient performance in
learning regular expressions",
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notes = "GP-98",
- }
Genetic Programming entries for
Nikolay Nikolaev
Vanio Slavov
Citations