The Donut Problem: Scalability and Generalization in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InCollection{kinnear:tackett,
  author =       "Walter Alden Tackett and Aviram Carmi",
  institution =  "HMSC",
  title =        "The Donut Problem: Scalability and Generalization in
                 Genetic Programming",
  booktitle =    "Advances in Genetic Programming",
  publisher =    "MIT Press",
  editor =       "Kenneth E. {Kinnear, Jr.}",
  year =         "1994",
  pages =        "143--176",
  chapter =      "7",
  URL =          "http://www.amazon.co.uk/Advances-Genetic-Programming-Complex-Adaptive/dp/0262111888",
  URL =          "http://cognet.mit.edu/sites/default/files/books/9780262277181/pdfs/9780262277181_chap7.pdf",
  keywords =     "genetic algorithms, genetic programming, Doughnut
                 problem",
  abstract =     "The Donut problem requires separating two toroidal
                 distributions (classes) which are interlocked like
                 links in a chain. The cross-section of each
                 distribution is Gaussian distributed with standard
                 deviation sigma. This problem possesses a variety of
                 pathological traits: the mean of each distribution, for
                 example, lies in the densest point of the other.",
  size =         "34 pages",
  notes =        "see also
                 http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/ftp.io.com/papers/.message
                 ICGA93.Donut.ps.Z - Preliminary version of Avi and
                 Walter's ICGA93 paper",
}

Genetic Programming entries for Walter Alden Tackett Aviram Carmi

Citations