Evolving choice structures for genetic programming

It is quite difficult but essential for Genetic Programming (GP) to evolve the choice structures. Traditional approaches usually ignore this issue. They define some “if-structures” functions according to their problems by combining “if-else” statement, conditional criterions and elemental functions together. Obviously, these if-structure functions depend on the specific problems and thus have much low reusability. Based on this limitation of GP, in this paper we propose a kind of termination criterion in the GP process named “Combination Termination Criterion” (CTC). By testing CTC, the choice structures composed of some basic functions independent to the problems can be evolved successfully. Theoretical analysis and experiment results show that our method can evolve the programs with choice structures effectively within an acceptable additional time.