Automatically Defined Features: The Simultaneous Evolution of 2-Dimensional Feature Detectors and an Algorithm for Using Them

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

@InCollection{kinnear:andre,
  title =        "Automatically Defined Features: The Simultaneous
                 Evolution of 2-Dimensional Feature Detectors and an
                 Algorithm for Using Them",
  author =       "David Andre",
  booktitle =    "Advances in Genetic Programming",
  publisher =    "MIT Press",
  editor =       "Kenneth E. {Kinnear, Jr.}",
  year =         "1994",
  pages =        "477--494",
  keywords =     "genetic algorithms, genetic programming",
  chapter =      "23",
  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_chap23.pdf",
  size =         "18 pages",
  abstract =     "Although automatically defined functions (ADFcts) with
                 genetic programming (GP) appear to have great utility
                 in a wide variety of domains, their application to the
                 automatic discovery of 2-dimensional features has been
                 only moderately successful [Koza 1993]. Boolean
                 functions of pixel inputs, although very general, may
                 not be the best representation for 2-dimensional
                 features. This chapter describes a method for the
                 simultaneous evolution of 2-dimensional hit-miss
                 matrices and an algorithm to use these matrices in
                 pattern recognition. Hit-miss matrices are templates
                 that can be moved over part of an input pattern to
                 check for a match. These matrices are evolved using a
                 2-dimensional genetic algorithm, while the algorithms
                 controlling the templates are evolved using GP. The
                 approach is applied to the problem of digit
                 recognition, and is found to be successful at
                 discovering individuals which can recognize very low
                 resolution digits. Possibilities for expansion into a
                 full-size character recognition system are discussed.",
  notes =        "

                 Mixture of GP and two dee GA",
}

Genetic Programming entries for David Andre

Citations