Genetic programming: parametric analysis of structure altering mutation techniques

We hypothesize that the relationship between parameter settings, specically parameters controlling mutation, and performance is non-linear in genetic programs. Genetic programming environments have few means for a priori determination of appropriate parameters values. The hypothesized nonlinear behavior of genetic programming creates diculty in selecting parameter values for many problems. In this paper we study three structure altering mutation techniques using parametric analysis on a problem with scalable complexity. We nd through parameter analysis that two of the three mutation types tested exhibit nonlinear behavior. Higher mutation rates cause a larger degree of nonlinear behavior as measured by tness and computational eort. Characterization of the mutation techniques using parametric analysis conrms the nonlinear behavior. In addition, we propose an extension to the existing parameter setting taxonomy to include commonly used structure altering mutation attributes. Final...

• Type: Conference
• Year: 2005
• Where: GECCO
• Authors: Alan Piszcz, Terence Soule
• Keywords: GECCO 2005, Mutations, Nonlinear Behavior, Parameter