Random Tree Generation for Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.2031

@InProceedings{iba:1996:rtgGP,
  author =       "Hitoshi Iba",
  title =        "Random Tree Generation for Genetic Programming",
  booktitle =    "Parallel Problem Solving from Nature IV, Proceedings
                 of the International Conference on Evolutionary
                 Computation",
  year =         "1996",
  editor =       "Hans-Michael Voigt and Werner Ebeling and 
                 Ingo Rechenberg and Hans-Paul Schwefel",
  series =       "LNCS",
  volume =       "1141",
  pages =        "144--153",
  address =      "Berlin, Germany",
  publisher_address = "Heidelberg, Germany",
  month =        "22-26 " # sep,
  publisher =    "Springer Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-61723-X",
  doi =          "doi:10.1007/3-540-61723-X_978",
  size =         "10 pages",
  abstract =     "This paper introduces a random tree generation
                 algorithm for GP (Genetic Programming). Generating
                 random trees is an essential part of GP. However, the
                 recursive method commonly used in GP does not
                 necessarily generate random trees, i.e the standard GP
                 initialisation procedure does not sample the space of
                 possible initial trees uniformly. This paper proposes a
                 truly random tree generation procedure for GP. Our
                 approach is grounded upon a bijection method, i.e., a
                 1-1 correspondence between a tree with n nodes and some
                 simple word composed by letters x and y. We show how to
                 use this correspondence to generate a GP tree and how
                 GP search is improved by using this randomness",
  notes =        "http://lautaro.fb10.tu-berlin.de/ppsniv.html
                 PPSN4

                 bijection, tree_by_dyck

                 Demonstrated on Mackey-Glass compared to 'grow' method
                 (not ramped half-and-half)",
  affiliation =  "Electrotechnical Laboratory (ETL) Machine Inference
                 Section 1-1-4 Umezono, Tsukuba Science City 305 Ibaraki
                 Japan 1-1-4 Umezono, Tsukuba Science City 305 Ibaraki
                 Japan",
}

Genetic Programming entries for Hitoshi Iba