Learning to sort by using evolution

This paper present a work where Genetic Programming (GP) was used to the task of evolving imperative sort programs. A variety of interesting lessons were learned. With proper selection of the primitives, sorting programs were evolved that are both general and non-trivial. Unique aspect of our approach is that we represent the individual programs with simple assembler code, rather than usual tree like structure. We also report the effect of different parameters on quality of the programs and time needed for finding the solution.