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

Created by W.Langdon from gp-bibliography.bib Revision:1.2704

@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, circuit layout evolution, combinational logic
                 circuits, connectivity, digital circuits, evolutionary
                 search, functionality, genome fitness, logic cells,
                 multi-objective fitness, rectangular array, two-fitness
                 strategy, circuit layout CAD, logic circuits, software
                 prototyping",
  ISBN =         "0-7695-0256-3",
  doi =          "doi:10.1109/EH.1999.785435",
  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 100percent
                 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 100percent 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 100percent 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