Evolving More Efficient Digital Circuits by Allowing Circuit Layout Evolution and Multi-Objective Fitness

Created by W.Langdon from gp-bibliography.bib Revision:1.2031

@InProceedings{Kalganova:1999:eh,
  author =       "T. Kalganova and J. Miller",
  title =        "Evolving More Efficient Digital Circuits by Allowing
                 Circuit Layout Evolution and Multi-Objective Fitness",
  booktitle =    "The First NASA/DoD Workshop on Evolvable Hardware",
  year =         "1999",
  editor =       "Adrian Stoica and Jason Lohn and Didier Keymeulen",
  pages =        "54--63",
  address =      "Pasadena, California",
  publisher_address = "1730 Massachusetts Avenue, N.W., Washington, DC
                 20036-1992, USA",
  month =        "19-21 " # jul,
  organisation = "Jet Propulsion Laboratory, California Institute of
                 Technology",
  publisher =    "IEEE Computer Society",
  keywords =     "genetic algorithms, genetic programming, evolvable
                 hardware",
  ISBN =         "0-7695-0256-3",
  abstract =     "We use evolutionary search to design combinational
                 logic circuits. The technique is based on evolving the
                 functionality and connectivity of a rectangular array
                 of logic cells whose dimension is defined by the
                 circuit layout. The main idea of this approach is to
                 improve quality of the circuits evolved by the genetic
                 algorithm (GA) by reducing the number of active gates
                 used. We accomplish this by combining two ideas: 1)
                 using multi-objective fitness function; 2) evolving
                 circuit layout. It will be shown that using these two
                 approaches allows us to increase the quality of evolved
                 circuits. The circuits are evolved in two phases.
                 Initially the genome fitness in given by the percentage
                 of output bits that are correct. Once 100\% functional
                 circuits have been evolved, the number of gates
                 actually used in the circuit is taken into account in
                 the fitness function. This allows us to evolve circuits
                 with 100\% functionality and minimise the number of
                 active gates in circuit structure. The population is
                 initialised with heterogeneous circuit layouts and the
                 circuit layout is allowed to vary during the
                 evolutionary process. Evolving the circuit layout
                 together with the function is one of the distinctive
                 features of proposed approach. The experimental results
                 show that allowing the circuit layout to be flexible is
                 useful when we want to evolve circuits with the
                 smallest number of gates used. We find that it is
                 better to use a fixed circuit layout when the objective
                 is to achieve the highest number of 100\% functional
                 circuits. The two-fitness strategy is most effective
                 when we allow a large number of generations.",
  notes =        "EH1999 http://cism.jpl.nasa.gov/events/nasa_eh/",
}

Genetic Programming entries for Tatiana Kalganova Julian F Miller