Introduction

Genetic Expression Programming (GEP) is an evolutionary algorithm that automatically creates computer programs. These computer programs can take many forms: they can be conventional mathematical models, neural networks, decision trees, sophisticated nonlinear models, logistic nonlinear regressors, nonlinear classifiers, complex polynomial structures, logic circuits and expressions, and so on. But irrespective of their complexity, all GEP programs are encoded in very simple linear structures - the chromosomes. These chromosomes are special because, no matter what, they always encode a valid computer program. So we can mutate them and then select the best ones to reproduce and then create more programs and so on, endlessly. This is, of course, one of the prerequisites for having a system evolving efficiently, searching for better and better solutions as it tries to solve a particular problem.