Program evolution by integrating edp and gp

Abstract. This paper discusses the performance of a hybrid system which consists of EDP and GP. EDP, Estimation of Distribution Pro-gramming, is the program evolution method based on the probabilistic model, where the probability distribution of a program is estimated by using a Bayesian network, and a population evolves repeating estimation of distribution and program generation without crossover and mutation. Applying the hybrid system of EDP and GP to various problems, we dis-covered some important tendencies in the behavior of this hybrid system. The hybrid system was not only superior to pure GP in a search per-formance but also had interesting features in program evolution. More tests revealed how and when EDP and GP compensate for each other. We show some experimental results of program evolution by the hybrid system and discuss the characteristics of both EDP and GP