Improving the evolvability of digital multipliers using embedded cartesian genetic programming and product reduction

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Abstract

Embedded Cartesian Genetic Programming (ECGP) is a form of Genetic Programming based on an acyclic directed graph representation. In this paper we investigate the use of ECGP together with a technique called Product Reduction (PR) to reduce the time required to evolve a digital multiplier. The results are compared with Cartesian Genetic Programming (CGP) with and without PR and show that ECGP improves evolvability and also that PR improves the performance of both techniques by up to eight times on the digital multiplier problems tested. © Springer-Verlag Berlin Heidelberg 2005.

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Walker, J. A., & Miller, J. F. (2005). Improving the evolvability of digital multipliers using embedded cartesian genetic programming and product reduction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3637 LNCS, pp. 131–142). Springer Verlag. https://doi.org/10.1007/11549703_13

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