Evolutionary Synthesis of Logic Circuits Using Information Theory

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Aguirre:2003:AIR,
  author =       "Arturo Hernandez Aguirre and 
                 Carlos A. {Coello Coello}",
  title =        "Evolutionary Synthesis of Logic Circuits Using
                 Information Theory",
  journal =      "Artificial Intelligence Review",
  year =         "2003",
  volume =       "20",
  number =       "3-4",
  pages =        "445--471",
  keywords =     "genetic algorithms, genetic programming, circuit
                 synthesis, computer-aided design, evolutionary
                 algorithms, evolvable hardware, information theory",
  language =     "English",
  publisher =    "Kluwer Academic Publishers",
  ISSN =         "0269-2821",
  annote =       "The Pennsylvania State University CiteSeerX Archives",
  bibsource =    "OAI-PMH server at citeseerx.ist.psu.edu",
  language =     "en",
  oai =          "oai:CiteSeerX.psu:10.1.1.378.9801",
  rights =       "Metadata may be used without restrictions as long as
                 the oai identifier remains attached to it.",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.378.9801",
  URL =          "http://hera.ugr.es/doi/14977278.pdf",
  URL =          "http://dx.doi.org/10.1023/B%3AAIRE.0000006603.98023.97",
  DOI =          "doi:10.1023/B:AIRE.0000006603.98023.97",
  abstract =     "In this paper, we propose the use of Information
                 Theory as the basis for designing a fitness function
                 for Boolean circuit design using Genetic Programming.
                 Boolean functions are implemented by replicating binary
                 multiplexers. Entropy-based measures, such as Mutual
                 Information and Normalised Mutual Information are
                 investigated as tools for similarity measures between
                 the target and evolving circuit. Three fitness
                 functions are built over a primitive one. We show that
                 the landscape of Normalized Mutual Information is more
                 amenable for being used as a fitness function than
                 simple Mutual Information. The evolutionary synthesised
                 circuits are compared to the known optimum size. A
                 discussion of the potential of the
                 Information-Theoretical approach is given.",
}

Genetic Programming entries for Arturo Hernandez-Aguirre Carlos Artemio Coello Coello

Citations