Applying Adaptive Grammar Based Genetic Programming in Evolving Recursive Programs

Genetic programming (GP) extends traditional genetic algorithms to automatically induce computer programs. GP has been applied in a wide range of applications such as software re-engineering, electrical circuits synthesis, knowledge engineering, and data mining. One of the most important and challenging research areas in GP is the investigation of ways to successfully evolve recursive programs. A recursive program is one that calls itself either directly or indirectly through other programs. Because recursions lead to compact and general programs and provide a mechanism for reusing program code, they facilitate GP to solve larger and more complicated problems. Nevertheless, it is commonly agreed that the recursive program learning problem is very difficult for GP. In this paper, we propose a technique to tackle the difficulties in learning recursive programs. The technique is incorporated into an adaptive Grammar Based Genetic Programming system (adaptive GBGP). A number of experiments have been performed to demonstrate that the system can evolve recursive programs efficiently and effectively.