Switching for Functional Localization of Genetic Network Programming
Shinji Eto, Kotaro Hirasawa, Jingle Hu · 2006
Many methods of generating behavior sequences of agents by evolution have been reported. A new evolutionary computation method named genetic network programming (GNP) has also been developed recently along with these trends. The aim of this paper is to build an artificial model to realize functional localization based on GNP considering the fact that the functional localization of the brain is realized in such a way that a different part of the brain corresponds to a different function. GNP has a directed graph structure suitable for realizing functional localization. In this paper, it is especially stated that the evolution of the switching function can be realized for functional localization of GNP using the self-sufficient garbage collector problem.