Fine-Grained Population Diversity Estimation for Genetic Programming Based Structure Identification

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3 Citations (Scopus)

Abstract

We here describe a novel formalism for estimating the structural similarity of formulas that are evolved by a genetic programming (GP) based identification process. This method takes into account several aspects of structure tree comparison that are particularly important in the context of evolutionary system identification; this similarity measure is used for measuring the genetic diversity among GP populations.

Original languageEnglish
Title of host publicationGECCO'08
Subtitle of host publicationProceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008
PublisherACM Sigevo
Pages1435-1436
Number of pages2
ISBN (Print)9781605581309
DOIs
Publication statusPublished - 2008
EventGenetic and Evolutionary Algorithms Conference GECCO 2008, Atlanta - Atlanta, GA, United States
Duration: 12 Jul 200816 Aug 2008

Publication series

NameGECCO'08: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008

Conference

ConferenceGenetic and Evolutionary Algorithms Conference GECCO 2008, Atlanta
CountryUnited States
CityAtlanta, GA
Period12.07.200816.08.2008

Keywords

  • Data mining
  • Genetic programming
  • Machine learning
  • Population diversity analysis
  • System identification

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