Rapid prediction of optimum population size in genetic programming using a novel genotype - Fitness correlation

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

    Abstract

    The main aim of landscape analysis has been to quantify the 'hardness' of problems. Early steps have been made towards extending this into Genetic Programming. However, few attempts have been made to extend the use of landscape analysis into the prediction of ways to make a problem easy, through the optimal setting of control parameters. This paper introduces a new class of landscape metrics, which we call 'Genotype-Fitness Correlations'. An example of this family of metrics is applied to six real-world regression problems. It is demonstrated that genotype-fitness correlations may be used to estimate optimum population sizes for the six problems. We believe that this application of a landscape metric as guidance in the setting of control parameters is an important step towards the development of an adaptive algorithm that can respond to the perceived landscape in 'real-time', i.e. during the evolutionary search process itself. Copyright 2008 ACM.
    Original languageEnglish
    Title of host publicationGECCO'08: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008|GECCO: Genet. Evolut. Comput. Conf. - Proc. Annu. Conf. Genet. Evolut. Comput.
    Place of PublicationNew York
    PublisherAssociation for Computing Machinery
    Pages1315-1322
    Number of pages7
    ISBN (Print)9781605581309
    Publication statusPublished - 2008
    Event10th Annual Genetic and Evolutionary Computation Conference, GECCO 2008 - Atlanta, GA
    Duration: 1 Jul 2008 → …

    Conference

    Conference10th Annual Genetic and Evolutionary Computation Conference, GECCO 2008
    CityAtlanta, GA
    Period1/07/08 → …

    Keywords

    • Control parameters
    • Genotype-fitness correlation
    • Landscape
    • Real-world

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