Dynamic observation of genotypic and phenotypic diversity for different symbolic regression gp variants

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4 Citations (Scopus)

Abstract

Understanding the relationship between selection, genotype-phenotype map and loss of population diversity represents an important step towards more effective genetic programming (GP) algorithms. This paper describes an approach to capture dynamic changes in this relationship. We analyze the frequency distribution of points in the diversity plane defined by structural and semantic similarity measures. We test our methodology using standard GP (SGP) on a number of test problems, as well as Offspring Selection GP (OS-GP), an algorithmic flavor where selection is explicitly focused towards adaptive change. We end with a discussion about the implications of diversity maintenance for each of the tested algorithms. We conclude that diversity needs to be considered in the context of fitness improvement, and that more diversity is not necessarily beneficial in terms of solution quality.

Original languageEnglish
Title of host publicationGECCO 2017 - Proceedings of the Genetic and Evolutionary Computation Conference Companion
PublisherAssociation for Computing Machinery, Inc
Pages1553-1558
Number of pages6
ISBN (Electronic)9781450349390
ISBN (Print)978-1-4503-4939-0
DOIs
Publication statusPublished - 15 Jul 2017
Event2017 Genetic and Evolutionary Computation Conference Companion, GECCO 2017 - Berlin, Germany
Duration: 15 Jul 201719 Jul 2017

Publication series

NameGECCO 2017 - Proceedings of the Genetic and Evolutionary Computation Conference Companion

Conference

Conference2017 Genetic and Evolutionary Computation Conference Companion, GECCO 2017
CountryGermany
CityBerlin
Period15.07.201719.07.2017

Keywords

  • Genetic and Phenotypic Diversity
  • Genetic Programming
  • Offspring Selection
  • Population Dynamics
  • Symbolic Regression

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