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

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@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

Citations