Reducing the number of fitness evaluations in graph genetic programming using a canonical graph indexed database.
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.
Niehaus
Jens
J
Visual Systems Automation GmbH, 59174 Kamen, Germany. niehaus@vsys.de
Igel
Christian
C
Banzhaf
Wolfgang
W
D000465:Algorithms; D005075:Biological Evolution; D003196:Computer Graphics; D030541:Databases, Genetic; D008957:Models, Genetic; D010641:Phenotype; D012984:Software