Abstract
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) and any time models (T7). We report halting probability, run time and functionality (including entropy of binary functions) of both halting and anytime programs. Turing complete program fitness landscapes, even with halt, scale poorly.
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Langdon, W.B. (2006). Mapping Non-conventional Extensions of Genetic Programming. In: Calude, C.S., Dinneen, M.J., Păun, G., Rozenberg, G., Stepney, S. (eds) Unconventional Computation. UC 2006. Lecture Notes in Computer Science, vol 4135. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11839132_14
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DOI: https://doi.org/10.1007/11839132_14
Publisher Name: Springer, Berlin, Heidelberg
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