Host: Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT)
We propose Genetic Programming(GP) with control nodes using conditional probability. In our method(GPCN_CP), each individual consists of some trees. In order to improve the efficiency, individuals in the next generation are generated by using genetic operations or conditional probability tables, where some individuals with high fitness values are used to evaluate conditional probability tables. We have implemented three methods, traditional GP, GP with control nodes(GPCN) and GPCN_CP, and these methods are applied to a garbage collector problem. Experimental results shows that GPCN_CP is more efficient than traditional GP and GPCN.
