Location Independent Pattern Recognition using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4020

  author =       "Markus M. Breunig",
  title =        "Location Independent Pattern Recognition using Genetic
  booktitle =    "Genetic Algorithms and Genetic Programming at Stanford
  year =         "1995",
  editor =       "John R. Koza",
  pages =        "29--38",
  address =      "Stanford, California, 94305-3079 USA",
  month =        "11 " # dec,
  publisher =    "Stanford Bookstore",
  keywords =     "genetic algorithms, genetic programming, ADF",
  ISBN =         "0-18-195720-5",
  URL =          "http://www.dbs.informatik.uni-muenchen.de/~breunig/HomepageResearch/Papers/PatternRecog.pdf",
  size =         "10 pages",
  abstract =     "This paper describes an application of genetic
                 programming. Programs able of recognising a pattern
                 independent of its location are evolved. Usually the
                 evolution of programs is controlled primarily by the
                 fitness evaluation function. This paper demonstrates
                 how genetic programming can be encouraged to evolve
                 programs with properties not being explicitly
                 considered in the fitness measure like location
                 independence. The measurements taken include the use of
                 automatically defined functions allowing the problem to
                 be decomposed into sub-functions, a special
                 implementation of iteration and carefully chosen
                 function and terminal sets. A main purpose was to
                 minimise the restrictions imposed on the solution, i.e.
                 giving the genetic programming as much freedom as
                 possible while still encouraging the desired
  notes =        "part of \cite{koza:1995:gagp}",

Genetic Programming entries for Markus M Breunig