Analysis of the effects of enhanced selection concepts for genetic programming based structure identification using fine-grained population diversity estimation

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Abstract

In this paper we use a formalism for estimating the structural similarity of formulas for measuring the genetic diversity among GP populations. As we show in the results section of this paper, population diversity differs a lot in the test runs depending on the selection schemata used; especially the use of strict offspring selection has a significant effect on the progress of the population's diversity.

Original languageEnglish
Title of host publicationGenetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication
PublisherACM Sigevo
Pages195-196
Number of pages2
ISBN (Print)9781450306904
DOIs
Publication statusPublished - 2011
Event13th Annual Genetic and Evolutionary Computation Conference, GECCO'11 - Dublin, Ireland
Duration: 12 Jul 201116 Jul 2011

Publication series

NameGenetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication

Conference

Conference13th Annual Genetic and Evolutionary Computation Conference, GECCO'11
CountryIreland
CityDublin
Period12.07.201116.07.2011

Keywords

  • data mining
  • genetic programming
  • machine learning
  • population dynamics
  • system identification

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