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Analysis of Schema Frequencies in Genetic Programming

  • Bogdan BurlacuEmail author
  • Michael Affenzeller
  • Michael Kommenda
  • Gabriel Kronberger
  • Stephan Winkler
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10671)

Abstract

Genetic Programming (GP) schemas are structural templates equivalent to hyperplanes in the search space. Schema theories provide information about the properties of subsets of the population and the behavior of genetic operators. In this paper we propose a practical methodology to identify relevant schemas and measure their frequency in the population. We demonstrate our approach on an artificial symbolic regression benchmark where the parts of the formula are already known. Experimental results reveal how solutions are assembled within GP and explain diversity loss in GP populations through the proliferation of repeated patterns.

Keywords

Genetic Programming Schema analysis Symbolic regression Tree pattern matching Evolutionary dynamics Loss of diversity 

Notes

Acknowledgements

The work described in this paper was done within the COMET Project Heuristic Optimization in Production and Logistics (HOPL), #843532 funded by the Austrian Research Promotion Agency (FFG).

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Bogdan Burlacu
    • 1
    • 2
    Email author
  • Michael Affenzeller
    • 1
    • 2
  • Michael Kommenda
    • 1
    • 2
  • Gabriel Kronberger
    • 1
  • Stephan Winkler
    • 1
  1. 1.Heuristic and Evolutionary Algorithms LaboratoryUniversity of Applied Sciences Upper AustriaHagenbergAustria
  2. 2.Institute for Formal Models and VerificationJohannes Kepler UniversityLinzAustria

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