Reducing the Number of Fitness Evaluations in Graph Genetic Programming Using a Canonical Graph Indexed Database

  • Authors:
  • Jens Niehaus;Christian Igel;Wolfgang Banzhaf

  • Affiliations:
  • Visual Systems Automation GmbH, 59174 Kamen, Germany niehaus@vsys.de;Institut für Neuroinformatik, Ruhr-Universität Bochum, 44780 Bochum, Germany igel@neuroinformatik.rub.de;Department of Computer Science, Memorial University of Newfoundland, St. John's, NL, A1B 3X5, Canada banzhaf@cs.mun.ca

  • Venue:
  • Evolutionary Computation
  • Year:
  • 2007

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Abstract

In this paper we describe the genetic programming system GGP operating on graphs and introduce the notion of graph isomorphisms to explain how they influence the dynamics of GP. It is shown empirically how fitness databases can improve the performance of GP and how mapping graphs to a canonical form can increase these improvements by saving considerable evaluation time.