Cartesian genetic programming for memristive logic circuits

Howard, Gerard David; Bull, Larry; Adamatzky, Andrew

Abstract

In this paper memristive logic circuits are evolved using Cartesian Genetic Programming. Graphs comprised of implication logic (IMP) nodes are compared to more ubiquitous NAND circuitry on a number of logic circuit problems and a robotic control task. Self-adaptive search parameters are used to provide each graph with autonomy with respect to its relative mutation rates. Results demonstrate that, although NAND-logic graphs are easier to evolve, IMP graphs carry benefits in terms of (i) numbers of memristors required (ii) the time required to process the graphs. © 2012 Springer-Verlag.

Citation

Howard, G. D., Bull, L., & Adamatzky, A. (2012). Cartesian genetic programming for memristive logic circuits. Lecture Notes in Artificial Intelligence, 7244 LNCS, 37-48. https://doi.org/10.1007/978-3-642-29139-5_4

• Journal Article Type: Conference Paper
• Publication Date: Apr 3, 2012
• Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
• Print ISSN: 0302-9743
• Electronic ISSN: 1611-3349
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 7244 LNCS
• Pages: 37-48
• Series Title: Lecture Notes in Computer Science
• DOI: https://doi.org/10.1007/978-3-642-29139-5_4
• Keywords: information systems applications, internet, computational biology, bioinformatics, computation, abstract devices, computer science, programming techniques, artificial intelligence, AI, robotics
• Public URL: https://uwe-repository.worktribe.com/output/950602
• Publisher URL: http://www.springerlink.com