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Coevolution in Cartesian Genetic Programming

  • Michaela Šikulová
  • Lukáš Sekanina
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7244)

Abstract

Cartesian genetic programming (CGP) is a branch of genetic programming which has been utilized in various applications. This paper proposes to introduce coevolution to CGP in order to accelerate the task of symbolic regression. In particular, fitness predictors which are small subsets of the training set are coevolved with CGP programs. It is shown using five symbolic regression problems that the (median) execution time can be reduced 2–5 times in comparison with the standard CGP.

Keywords

Cartesian genetic programming Coevolution Symbolic regression 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Michaela Šikulová
    • 1
  • Lukáš Sekanina
    • 1
  1. 1.Faculty of Information Technology, IT4Innovations Centre of ExcellenceBrno University of TechnologyBrnoCzech Republic

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