Genetic Network Programming with Control Nodes considering Breadth and Depth

Many methods of generating behavior sequences of agents by evolution have been reported. A new evolutionary computation method named genetic network programming (GNP) has been also developed recently along with these trends. GNP has a directed graph structure and the search for obtaining optimal GNP becomes difficult when the scale of GNP is large. The aim of this paper is to find a well structured GNP considering Breadth and Depth of GNP searching. It has been shown that the proposed method is efficient compared with conventional GNPs from simulations using a garbage collector problem.