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Fitness Distance Correlation in Structural Mutation Genetic Programming

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2610)

Abstract

A new kind of mutation for genetic programming based on the structural distance operators for trees is presented in this paper. We firstly describe a new genetic programming process based on these operators (we call it structural mutation genetic programming). Then we use structural distance to calculate the fitness distance correlation coefficient and we show that this coefficient is a reasonable measure to express problem difficulty for structural mutation genetic programming for the considered set of problems, i.e. unimodal trap functions, royal trees and MAX problem.

Keywords

Genetic Programming Genetic Operator Fitness Landscape Structural Distance Structural Operation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  1. 1.Computer Science InstituteUniversity of LausanneLausanneSwitzerland
  2. 2.I3S LaboratoryUniversity of NiceSophia AntipolisFrance

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