Evolution of Learning Rules for Hard Learning Problems

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Ibrahim Kuscu",
  title =        "Evolution of Learning Rules for Hard Learning
  booktitle =    "Evolutionary Programming V: Proceedings of the Fifth
                 Annual Conference on Evolutionary Programming",
  year =         "1996",
  editor =       "Lawrence J. Fogel and Peter J. Angeline and 
                 Thomas Baeck",
  address =      "San Diego",
  publisher_address = "Cambridge, MA, USA",
  month =        feb # " 29-" # mar # " 3",
  publisher =    "MIT Press",
  keywords =     "genetic algorithms, genetic programming, Supervised
                 Learning, Three Monk's Problems, Parity Problems",
  ISBN =         "0-262-06190-2",
  broken =       "http://www.cogs.susx.ac.uk/users/ibrahim/epconf.ps",
  URL =          "http://citeseer.ist.psu.edu/rd/6296950%2C184922%2C1%2C0.25%2CDownload/http://citeseer.ist.psu.edu/cache/papers/cs/734/http:zSzzSzwww.cogs.susx.ac.ukzSzuserszSzibrahimzSzepconf.pdf/evolution-of-learning-rules.pdf",
  URL =          "http://citeseer.ist.psu.edu/184922.html",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=",
  size =         "9 pages",
  abstract =     "Recent experiments with a genetic-based encoding
                 schema are presented as a potentially useful tool in
                 discovering learning rules by means of evolution. The
                 representation strategy is similar to that used in
                 genetic programming(GP) but it employs only a fixed set
                 of functions to solve a variety of problems. In this
                 paper, three Monk's and parity problems are tested. The
                 results indicate the usefulness of the encoding schema
                 in discovering learning rules for hard learning
                 problems. The problems and future research directions
                 are discussed within the context of GP practices.",
  notes =        "EP-96

                 Details from

Genetic Programming entries for Ibrahim Kuscu