Towards identifying salient patterns in genetic programming individuals

András Joó*, Juan Pablo Neirotti

*Corresponding author for this work

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

Abstract

A practical method for the offline extraction and analysis of salient patterns from tree-based genetic programming (GP) individuals is proposed. The method is contrasted with Tackett's algorithm [7] and it is shown that relying solely on frequency and fitness profiles for the salient pattern identification can be misleading. To amend Tackett's work a formula for measuring saliency is proposed. A method for separating inert and salient patterns is also discussed.

Original languageEnglish
Title of host publicationProceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO '09
Place of PublicationNew York, NY (US)
PublisherACM
Pages1885-1886
Number of pages2
ISBN (Print)978-1-60558-325-9
DOIs
Publication statusPublished - 8 Jul 2009
Event11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009 - Montreal, QC, Canada
Duration: 8 Jul 200912 Jul 2009

Conference

Conference11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
CountryCanada
CityMontreal, QC
Period8/07/0912/07/09

Keywords

  • genetic programming
  • patterns
  • tree-mining

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  • Cite this

    Joó, A., & Neirotti, J. P. (2009). Towards identifying salient patterns in genetic programming individuals. In Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO '09 (pp. 1885-1886). ACM. https://doi.org/10.1145/1569901.1570217