- 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",
- keywords = "genetic algorithms, genetic programming, Doughnut problem",
-
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",
-
DOI = "
doi:10.7551/mitpress/1108.003.0012",
- size = "34 pages",
- 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.",
-
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
Part of \cite{kinnear:book}",
