Session:

MSA - Military and Security Applications of Evolutionary Computation

Title:

Parametric Regression Through Genetic Programming

Authors:

Edwin Roger Banks
James C. Hayes
Edwin Nunez

Abstract:

Parametric regression in genetic programming can substantially speed up the search for solutions. In this paper parametric regression is applied to a minimum-time-to-target problem. The solution is equivalent to the classical brachistochrone. Two formulations were tried: a parametric regression and the classical symbolic regression formulation. The parametric approach was superior under a wide variety of conditions. We speculate the parametric approach is more generally applicable to other problems and suggest areas for more research.