Towards Automatic Discovery of Building Blocks in Genetic Programming

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

@InProceedings{rosca:1995:tadbb,
  author =       "Justinian Rosca",
  title =        "Towards Automatic Discovery of Building Blocks in
                 Genetic Programming",
  booktitle =    "Working Notes for the AAAI Symposium on Genetic
                 Programming",
  year =         "1995",
  editor =       "E. V. Siegel and J. R. Koza",
  pages =        "78--85",
  address =      "MIT, Cambridge, MA, USA",
  publisher_address = "445 Burgess Drive, Menlo Park, CA 94025, USA",
  month =        "10--12 " # nov,
  publisher =    "AAAI",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.aaai.org/Papers/Symposia/Fall/1995/FS-95-01/FS95-01-011.pdf",
  URL =          "ftp://ftp.cs.rochester.edu/pub/u/rosca/gp/95.aaai.fs.ps.gz",
  URL =          "http://www.aaai.org/Library/Symposia/Fall/fs95-01.php",
  size =         "8 pages",
  abstract =     "This paper presents an algorithm for the discovery of
                 building blocks in genetic programming (GP) called {\it
                 adaptive representation through learning} (ARL). The
                 central idea of ARL is the adaptation of the problem
                 representation, by extending the set of terminals and
                 functions with a set of evolvable subroutines. The set
                 of subroutines extracts common knowledge emerging
                 during the evolutionary process and acquires the
                 necessary structure for solving the problem. ARL
                 supports subroutine creation and deletion. Subroutine
                 creation or discovery is performed automatically based
                 on the differential parent-offspring fitness and block
                 activation. Subroutine deletion relies on a utility
                 measure similar to schema fitness over a window of past
                 generations. The technique described is tested on the
                 problem of controlling an agent in a dynamic and
                 non-deterministic environment. The automatic discovery
                 of subroutines can help scale up the GP technique to
                 complex problems.",
  notes =        "AAAI-95f GP. Part of \cite{siegel:1995:aaai-fgp} {\em
                 Telephone:} 415-328-3123 {\em Fax:} 415-321-4457 {\em
                 email} info@aaai.org {\em URL:} http://www.aaai.org/
                 Fuller description in \cite{rosca:1996:aigp2}",
}

Genetic Programming entries for Justinian Rosca

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