Abstract
A cell array is a proposed type of custom FPGA, where digital circuits can be formed from interconnected configurable cells. In this paper we have presented a means by which CGP might be adapted to evolve configurations of a proposed cell array. As part of doing so, we have suggested an additional genetic operator that exploits modularity by copying sections of the genome within a solution, and investigated its efficacy. Additionally, we have investigated applying selection pressure for parsimony during functional evolution, rather than in a subsequent stage as proposed in other work. Our results show that solutions to benchmark problems can be evolved with a good degree of efficiency, and that compact solutions can be found with no significant impact on the required number of circuit evaluations.
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Bremner, P., Samie, M., Dragffy, G., Pipe, A.G., Liu, Y. (2011). Evolving Cell Array Configurations Using CGP. In: Silva, S., Foster, J.A., Nicolau, M., Machado, P., Giacobini, M. (eds) Genetic Programming. EuroGP 2011. Lecture Notes in Computer Science, vol 6621. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20407-4_7
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DOI: https://doi.org/10.1007/978-3-642-20407-4_7
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