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

Publikation: Beitrag in Buch/Bericht/TagungsbandKonferenzbeitragBegutachtung

5 Zitate (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.

OriginalspracheEnglisch
TitelGECCO 2017 - Proceedings of the Genetic and Evolutionary Computation Conference Companion
Herausgeber (Verlag)Association for Computing Machinery, Inc
Seiten1553-1558
Seitenumfang6
ISBN (elektronisch)9781450349390
ISBN (Print)978-1-4503-4939-0
DOIs
PublikationsstatusVeröffentlicht - 15 Jul 2017
Veranstaltung2017 Genetic and Evolutionary Computation Conference Companion, GECCO 2017 - Berlin, Deutschland
Dauer: 15 Jul 201719 Jul 2017

Publikationsreihe

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

Konferenz

Konferenz2017 Genetic and Evolutionary Computation Conference Companion, GECCO 2017
Land/GebietDeutschland
OrtBerlin
Zeitraum15.07.201719.07.2017

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