Evolving Digital Circuits using Multi Expression Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "Mihai Oltean and Crina Grosan",
  title =        "Evolving Digital Circuits using Multi Expression
  booktitle =    "Proceedings of the 2004 NASA/DoD Conference on
                 Evolvable Hardware",
  year =         "2004",
  editor =       "Ricardo S. Zebulum and David Gwaltney and 
                 Gregory Horbny and Didier Keymeulen and Jason Lohn and 
                 Adrian Stoica",
  pages =        "87--97",
  address =      "Seattle",
  month =        "24-26 " # jun,
  publisher =    "IEEE Press",
  email =        "moltean@cs.ubbcluj.ro",
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming, multi expression programming,
                 digital circuits",
  URL =          "http://www.cs.ubbcluj.ro/~moltean/oltean_eh04.pdf",
  DOI =          "doi:10.1109/EH.2004.1310814",
  size =         "8 pages",
  abstract =     "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.",
  notes =        "EH2004

                 NB online version oltean_eh04.pdf (Nov 2006) is 8 pages
                 long rather than the four orginally suggested. Double

                 Also available at www.mep.cs.ubbcluj.ro (including the
                 source code).",

Genetic Programming entries for Mihai Oltean Crina Grosan