The Dynamics of Biased Inductive Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{nikolaev:1998:dbiGP,

• author = "Nikolay I. Nikolaev and Vanio Slavov",
• title = "The Dynamics of Biased Inductive Genetic Programming",
• booktitle = "Genetic Programming 1998: Proceedings of the Third Annual Conference",
• year = "1998",
• 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",
• pages = "260--268",
• address = "University of Wisconsin, Madison, Wisconsin, USA",
• publisher_address = "San Francisco, CA, USA",
• month = "22-25 " # jul,
• publisher = "Morgan Kaufmann",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "1-55860-548-7",
• broken = "http://homepages.gold.ac.uk/nikolaev/gp98.ps.gz",
• URL = "http://citeseer.ist.psu.edu/cache/papers/cs/26570/http:zSzzSzwww.niss.gov.uazSzCenterzSzarticleszSzpaperszSzeurogp98.pdf/nikolaev98concepts.pdf",
• URL = "http://citeseer.ist.psu.edu/cache/papers/cs/23849/http:zSzzSzhomepages.gold.ac.ukzSznikolaevzSzgp98.pdf/the-dynamics-of-biased.pdf",
• URL = "http://citeseer.ist.psu.edu/468314.html",
• size = "8 pages",
• 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",
• notes = "GP-98",

}

Genetic Programming entries for Nikolay Nikolaev Vanio Slavov

Citations