Graph Structured Program Generation Using Evolutionary Algorithm Considering Program Size

Abstract

Today, a lot of automatic programming techniques have been proposed and applied in various fields. Graph Structured Program Evolution (GRAPE) is one of the recent automatic programming techniques. The representation of GRAPE is graph structure, therefore it can represent complex programs using its graph structure. GRAPE succeeds in generating the complex programs automatically. The generation alternation model of GRAPE is usually used minimal generation gap (MGG) which is not considered the evolution of program size. Therefore, it would not be search various program sizes. In this paper, a new evolutionary algorithm for GRAPE, called Evolutionary Algorithm Considering Program Size (EACP), is proposed. EACP maintains the diversity of program size in the population by using particular fitness assignment and generation alternation. We apply EACP to three test problems, factorial, exponentiation and sorting a list. And we show the effectiveness of EACP and confirm evolution of maintaining the diversity of program size.