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.

graph representation, genetic programming, graph isomorphism, neutrality, fitness database
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© 2007 by the Massachusetts Institute of Technology
2007
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