Genetic Evolution of Machine Language Software
Ronald L. Crepeau, Nccosc Rdte · 2006
Genetic Programming (GP) has a proven capability to routinely evolve software that provides a solution function for the specified problem. Prior work in this area has been based upon the use of relatively small sets of pre-defined operators and terminals germane to the problem domain. This paper reports on GP experiments involving a large set of general purpose operators and terminals. Specifically, a microprocessor architecture with 660 instructions and 255 bytes of memory provides the operators and terminals for a GP environment. Using this environment, GP is applied to the beginning programmer problem of generating a desired string output, e.g., Hello World. Results are presented on: the feasibility of using this large operator set and architectural representation; and, the computations required to breed string outputting programs vs. the size of the string and the GP parameters employed.