Inductive Genetic Programming with Decision Trees

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Nikolay I. Nikolaev and Vanio Slavov",
  title =        "Inductive Genetic Programming with Decision Trees",
  journal =      "Intelligent Data Analysis",
  volume =       "2",
  pages =        "31--44",
  year =         "1998",
  number =       "1-4",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "",
  abstract =     "This article proposes a study of inductive Genetic
                 Programming with Decision Trees (GPDT). The theoretical
                 underpinning is an approach to the development of
                 fitness functions for improving the search guidance.
                 The approach relies on analysis of the global fitness
                 landscape structure with a statistical correlation
                 measure. The basic idea is that the fitness landscape
                 could be made informative enough to enable efficient
                 search navigation. We demonstrate that by a careful
                 design of the fitness function the global landscape
                 becomes smoother, its correlation increases, and
                 facilitates the search. Another claim is that the
                 fitness function has not only to mitigate navigation
                 difficulties, but also to guarantee maintenance of
                 decision trees with low syntactic complexity and high
                 predictive accuracy.",

Genetic Programming entries for Nikolay Nikolaev Vanio Slavov