Abstract
This paper presents for the first time the application of Cartesian Genetic Programming to the evolution of machine code for a simple implementation of a MOVE processor. The effectiveness of the algorithm is demonstrated by evolving machine code for a 4-bit multiplier with three different levels of parallelism. The results show that 100% successful solutions were found by CGP and by further optimising the size of the solutions, it is possible to find efficient implementations of the 4-bit multiplier that have the potential to be "human competitive". Further analysis of the results revealed that the structure of some solutions followed a known general design methodology. © 2010 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Walker, J. A., Liu, Y., Tempesti, G., & Tyrrell, A. M. (2010). Automatic code generation on a MOVE processor using cartesian genetic programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6274 LNCS, pp. 238–249). https://doi.org/10.1007/978-3-642-15323-5_21
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