Genetic Network Programming(GNP) which has been developed for dealing with problems in dynamic envi-ronments is a newly propose devolutionary approach with the data structure of directed graphs. GNP has been used in many different areas such as datami...
Genetic Network Programming(GNP) which has been developed for dealing with problems in dynamic envi-ronments is a newly propose devolutionary approach with the data structure of directed graphs. GNP has been used in many different areas such as datamining, extracting trading rules of stock markets, elevator supervised control systems, etc and has obtained some out standing results. Focusing on GNP’s distinguishing expressionability of the graph structure, this paper proposes a method named Genetic Network Program-ming with General Individual Recon struction(GNP with GIR) which reconstructs the gene of randomly selected individuals and then under goes the special genetic operations by using the transition information of betterin dividuals. The unique indi-vidual reconstruction and genetic operations make individuals not only learn the experiences of better individuals but also strength enexploratio and exploration ability. GNP with GIR will be applied to the tile-world which is an excellent bench mark for evaluating the proposed architecture. The performances of GNP with GIR will becompared with conventional GNP demonstrating its superiority.