Use of a multi-objective fitness function to improve cartesian genetic programming circuits

James A. Hilder, James Alfred Walker, Andy M. Tyrrell · 2010

This paper describes an approach of using a multi-objective fitness function to improve the performance of digital circuits evolved using CGP. Circuits are initially evolved for correct functionality using conventional CGP before the NSGA-II algorithm is used to extract circuits which are more efficient in terms of design complexity and delay. This approach is used to evolve typical digital-system building block circuits with results compared to standard-CGP, other evolutionary methods and conventional designs.

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