Ancestral networks in evolutionary algorithms

Karthik Kuber, Stuart W. Card, Kishan G. Mehrotra, Chilukuri K. Mohan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The behaviors of populations in evolutionary algorithms can be understood in terms of the dynamics of network models whose nodes represent individuals in the population. This paper explores "ancestral networks" in which connections indicate the proximity of the nearest common ancestor of two nodes. Preliminary experimental results show that the formation of large components in such an ancestral network model can be used to identify potential convergence, and to determine when randomly reseeding part of a population can prove beneficial.

Original languageEnglish (US)
Title of host publicationGECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference
PublisherAssociation for Computing Machinery
Pages115-116
Number of pages2
ISBN (Print)9781450328814
DOIs
StatePublished - Jan 1 2014
Event16th Genetic and Evolutionary Computation Conference, GECCO 2014 - Vancouver, BC, Canada
Duration: Jul 12 2014Jul 16 2014

Publication series

NameGECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference

Other

Other16th Genetic and Evolutionary Computation Conference, GECCO 2014
CountryCanada
CityVancouver, BC
Period7/12/147/16/14

Keywords

  • Ancestral networks
  • Convergence detection
  • Genetic algorithms
  • Network science
  • Reseeding

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Applied Mathematics

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  • Cite this

    Kuber, K., Card, S. W., Mehrotra, K. G., & Mohan, C. K. (2014). Ancestral networks in evolutionary algorithms. In GECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference (pp. 115-116). (GECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference). Association for Computing Machinery. https://doi.org/10.1145/2598394.2598481