Automatic Code Generation on a MOVE Processor Using Cartesian Genetic Programming

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@InProceedings{Walker:2010:ICESb,

• author = "James Alfred Walker and Yang Liu and Gianluca Tempesti and Andy M. Tyrrell",
• title = "Automatic Code Generation on a MOVE Processor Using Cartesian Genetic Programming",
• booktitle = "Proceedings of the 9th International Conference Evolvable Systems: From Biology to Hardware, ICES 2010",
• year = "2010",
• editor = "Gianluca Tempesti and Andy M. Tyrrell and Julian F. Miller",
• series = "Lecture Notes in Computer Science",
• volume = "6274",
• pages = "238--249",
• address = "York",
• month = sep # " 6-8",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, cartesian genetic programming",
• isbn13 = "978-3-642-15322-8",
• DOI = "doi:10.1007/978-3-642-15323-5_21",
• 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 100percent 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.",
• affiliation = "Intelligent Systems Group, Department of Electronics, University of York, Heslington, York, YO10 5DD UK",

}

Genetic Programming entries for James Alfred Walker Yang Liu Gianluca Tempesti Andrew M Tyrrell

Citations