Power of Brute-Force Search in Strongly-Typed Inductive Functional Programming Automation

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@InProceedings{Katayama:2004:PRICAI,
  author =       "Susumu Katayama",
  title =        "Power of Brute-Force Search in Strongly-Typed
                 Inductive Functional Programming Automation",
  booktitle =    "8th Pacific Rim International Conference on Artificial
                 Intelligence, PRICAI 2004",
  year =         "2004",
  editor =       "Chengqi Zhang and Hans W. Guesgen and Wai-Kiang Yeap",
  volume =       "3157",
  series =       "Lecture Notes in Computer Science",
  pages =        "75--84",
  address =      "Auckland, New Zealand",
  month =        aug # " 9-13",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-540-22817-2",
  URL =          "http://nautilus.cs.miyazaki-u.ac.jp/~skata/abstPRICAI04.html",
  URL =          "http://dx.doi.org/10.1007/978-3-540-28633-2_10",
  DOI =          "doi:10.1007/978-3-540-28633-2_10",
  size =         "10 pages",
  abstract =     "A successful case of applying brute-force search to
                 functional programming automation is presented and
                 compared with a conventional genetic programming
                 method. From the information of the type and the
                 property that should be satisfied, this algorithm is
                 able to find automatically the shortest Haskell program
                 using the set of function components (or library)
                 configured beforehand, and there is no need to design
                 the library every time one requests a new functional
                 program.

                 According to the presented experiments, programs
                 consisted of several function applications can be found
                 within some seconds even if we always use the library
                 designed for general use. In addition, the proposed
                 algorithm can efficiently tell the number of possible
                 functions of given size that are consistent with the
                 given type, and thus can be a tool to evaluate other
                 methods like genetic programming by providing the
                 information of the baseline performance.",
}

Genetic Programming entries for Susumu Katayama

Citations