Genetic Programming with Guaranteed Constraints

Genetic programming is a powerful technique for automatically generating program code from a description of the desired functionality. However it is frequently distrusted by users because the programs are generated with reference to a training set, and there is no formal guarantee that the generated programs will operate as intended outside of this training set. This paper describes a way of including constraints into the fitness function of a genetic programming system, so that the evolution is guided towards a solution which satisfies those constraints and so that a check can be made when a solution satisfies those constraints. This is applied to a problem in mobile robotics.