Comparison between genetic network programming and genetic programming using evolution of ant's behaviors

Abstract

Recently, many methods of evolutionary computation such as Genetic Algorithm (GA) and Genetic Programming (GP) have been developed as a basic tool for modeling and optimizing the complex systems. Generally speaking, GA has the genome of string structure, while the genome in GP is the tree structure. Therefore, GP is suitable to construct the complicated programs, which can be applied to many real world problems. But, GP is sometimes difficult to search for a solution because of its bloat and introns. In this paper, a new evolutionary method named Genetic Network Programming (GNP), whose genome is network structure is proposed to overcome the low searching efficiency of GP and is applied to the problem on the evolution of behaviors of ants in order to study the effectiveness of GNP. In addition, the comparison of the performances between GNP and GP is carried out in simulations on ants behaviors.