``Six Degrees of Separation'' in Boolean Function Networks with Neutrality

Created by W.Langdon from gp-bibliography.bib Revision:1.4333

  author =       "Tina Yu",
  title =        "``Six Degrees of Separation'' in Boolean Function
                 Networks with Neutrality",
  editor =       "R. Poli and S. Cagnoni and M. Keijzer and E. Costa and 
                 F. Pereira and G. Raidl and S. C. Upton and 
                 D. Goldberg and H. Lipson and E. {de Jong} and J. Koza and 
                 H. Suzuki and H. Sawai and I. Parmee and M. Pelikan and 
                 K. Sastry and D. Thierens and W. Stolzmann and 
                 P. L. Lanzi and S. W. Wilson and M. O'Neill and C. Ryan and 
                 T. Yu and J. F. Miller and I. Garibay and G. Holifield and 
                 A. S. Wu and T. Riopka and M. M. Meysenburg and 
                 A. W. Wright and N. Richter and J. H. Moore and 
                 M. D. Ritchie and L. Davis and R. Roy and M. Jakiela",
  booktitle =    "GECCO 2004 Workshop Proceedings",
  year =         "2004",
  month =        "26-30 " # jun,
  address =      "Seattle, Washington, USA",
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming",
  URL =          "http://www.cs.mun.ca/~tinayu/Publications_files/GECCO2004.pdf",
  URL =          "http://www.cs.mun.ca/~tinayu/index_files/addr/public_html/NuE002.pdf",
  URL =          "http://www.cs.bham.ac.uk/~wbl/biblio/gecco2004/WNUE003.pdf",
  size =         "12 pages",
  abstract =     "We analyse two Boolean function networks with
                 different degrees of neutrality. The results show that
                 the one with explicit neutrality is a small-world
                 network where each pair of possible solutions has a
                 short distance and most of the possible solutions are
                 highly clustered. These network structural properties
                 owe their existence to the ``short cuts'' introduced by
                 redundant genes in the genotypes. We explain some
                 important small-world network structures, such as
                 clusters, hubs and power law link distribution. These
                 properties have potential to be useful in designing
                 efficient evolutionary algorithms to navigate search in
                 the network.",
  notes =        "GECCO-2004WKS Distributed on CD-ROM at GECCO-2004

                 3 bit parity, XOR",

Genetic Programming entries for Tina Yu