Empirical Analysis of Schemata in Genetic Programming using Maximal Schemata and MSG

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Smart:2008:cec,
  author =       "Will Smart and Mengjie Zhang",
  title =        "Empirical Analysis of Schemata in Genetic Programming
                 using Maximal Schemata and MSG",
  booktitle =    "2008 IEEE World Congress on Computational
                 Intelligence",
  year =         "2008",
  editor =       "Jun Wang",
  pages =        "2983--2990",
  address =      "Hong Kong",
  month =        "1-6 " # jun,
  organization = "IEEE Computational Intelligence Society",
  publisher =    "IEEE Press",
  isbn13 =       "978-1-4244-1823-7",
  file =         "EC0665.pdf",
  DOI =          "doi:10.1109/CEC.2008.4631200",
  abstract =     "Plenteous research studies schemata in Genetic
                 Programming (GP), though little of it is been
                 empirical, due to the vast numbers of typical schemata
                 in even small populations. In this research, we define
                 maximal schemata, and extend our Trips algorithm to the
                 more general Max-Schema-Growth (MSG) algorithm,
                 applicable to a wider range of schema forms (Trips only
                 handles standard fragment schemata). We present MSG
                 specialised to work with unordered-fragments schemata
                 (tree-fragments with unordered functions), and compare
                 the number of maximal schemata found of these two
                 forms. For most maximal fragments, another maximal
                 fragment was also found that differed only by the
                 orders of function node arguments. We conclude that
                 maximal unordered-fragments may represent a greater
                 range of common patterns between programs than standard
                 maximal fragments, though the greater reach comes at a
                 price with a severe increase in the time taken by the
                 algorithm.",
  keywords =     "genetic algorithms, genetic programming",
  notes =        "WCCI 2008 - A joint meeting of the IEEE, the INNS, the
                 EPS and the IET.",
}

Genetic Programming entries for Will Smart Mengjie Zhang

Citations