Artificial Intelligence

    

Evolving Digital Circuits using Multi Expression Programming

Authors: Mihai Oltean, Crina Grosan

Multi Expression Programming (MEP) is a Genetic Programming (GP) variant that uses linear chromosomes for solution encoding. A unique MEP feature is its ability of encoding multiple solutions of a problem in a single chromosome. These solutions are handled in the same time complexity as other techniques that encode a single solution in a chromosome. In this paper, MEP is used for evolving digital circuits. MEP is compared to Cartesian Genetic Programming (CGP) – a technique widely used for evolving digital circuits – by using several well-known problems in the field of electronic circuit design. Numerical experiments show that MEP outperforms CGP for the considered test problems.

Comments: NASA/DoD Conference on Evolvable Hardware, 24-26 June, Seattle, Edited by R. Zebulum (et. al), pages 87-90, IEEE Press, NJ, 2004

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[v1] 2022-02-14 01:46:16

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