Mapping non-conventional extensions of genetic programming

摘要

Conventional genetic programming research excludes memory and iteration. We have begun an extensive analysis of the space through which GP or other unconventional AI approaches search and extend it to consider explicit program stop instructions (T8), including Markov analysis and any time models (T7). We report halting probability, run time and functionality (including entropy of binary functions) of both halting and anytime programs. Irreversible Turing complete program fitness landscapes, even with halt, scale poorly however loops lock-in variation allowing more interesting functions.