Cartesian Genetic Programming in a changing environment

Abstract

Evolutionary algorithm are prevalently being used in static environments. In a dynamically changing environment an evolutionary algorithm must be also able to cope with the changes of the environment. This paper describes an algorithm based on Cartesian Genetic Programming (CGP) that is used to design and optimise a solution in a simulated symbolic regression problem in a changing environment. A modified version of the Age-Layered Population Structure (ALPS) algorithm is being used in cooperation with CGP. It is shown that the usage of ALPS can improve the performance on of CGP when solving problems in a changing environment.