Evolving cell array configurations using CGP

Bremner, Paul; Samie, Mohammad; Dragffy, Gabriel; Pipe, Anthony G.; Liu, Yang

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. © 2011 Springer-Verlag.

• Presentation Conference Type: Conference Paper (published)
• Publication Date: May 13, 2011
• Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
• Print ISSN: 0302-9743
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 6621 LNCS
• Pages: 73-84
• Series Title: Lecture Notes in Computer Science
• Series Number: 6621
• DOI: https://doi.org/10.1007/978-3-642-20407-4_7
• Keywords: programming techniques, computation by abstract devices, algorithm analysis and problem complexity, pattern recognition, artificial intelligence, robotics, computational biology, bioinformatics, cell array configurations, CGP
• Public URL: https://uwe-repository.worktribe.com/output/967330
• Publisher URL: http://dx.doi.org/10.1007/978-3-642-20407-4_7
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