Versatile Function GPA

This herein presented paper is dedicated to the introduction of the continuous versatile function Genetic Programming Algorithm (GPA) developed with respect to BigData processing. The basic structure of this hierarchical evolutionary algorithm and examples of versatile functions are presented.On the basis of experiments with the hybrid evolutionary algorithm (hybrid EA) providing symbolic regression of precomputed Lorenz attractor system data representing hybrid EA’s behaviour, a discussion of examples of an obtained solution is presented. The versatile function concept GPA is applicable, but it requires the hybrid evolutionary algorithm application, as is demonstrated in the paper.