Evolving cell array configurations using CGP

  • Authors:

  • Paul Bremner;Mohammad Samie;Gabriel Dragffy;Anthony G. Pipe1;Yang Liu

  • Affiliations:

  • Bristol Robotics Laboratory, University of the West of England, Bristol;Bristol Robotics Laboratory, University of the West of England, Bristol;Bristol Robotics Laboratory, University of the West of England, Bristol;Bristol Robotics Laboratory, University of the West of England, Bristol;Intelligent Systems Group, Department of Electronics, University of York, Heslington, York

  • Venue:
  • EuroGP'11 Proceedings of the 14th European conference on Genetic programming
  • Year:
  • 2011

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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.