A Scheme for the Evolution of Feedforward Neural Networks using BNF-Grammar Driven Genetic Programming

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@InProceedings{oai:CiteSeerPSU:573568,
  title =        "A Scheme for the Evolution of Feedforward Neural
                 Networks using {BNF}-Grammar Driven Genetic
                 Programming",
  author =       "Athanasios D. Tsakonas and Georgios Dounias",
  year =         "2002",
  citeseer-isreferencedby = "oai:CiteSeerPSU:98726",
  citeseer-references = "oai:CiteSeerPSU:46964; oai:CiteSeerPSU:63750;
                 oai:CiteSeerPSU:17850; oai:CiteSeerPSU:267599;
                 oai:CiteSeerPSU:271953; oai:CiteSeerPSU:186821;
                 oai:CiteSeerPSU:30755",
  annote =       "The Pennsylvania State University CiteSeer Archives",
  language =     "en",
  oai =          "oai:CiteSeerPSU:573568",
  rights =       "unrestricted",
  booktitle =    "European Symposium on Intelligent Technologies, Hybrid
                 Systems and their implementation on Smart Adaptive
                 Systems",
  address =      "Algarve, Portugal",
  month =        "19-21 " # sep,
  organisation = "European Network of Excellence EUNITE",
  keywords =     "genetic algorithms, genetic programming, pima
                 indians",
  URL =          "http://www2.ba.aegean.gr/members/tsakonas/Algarve2002.pdf",
  URL =          "http://citeseer.ist.psu.edu/573568.html",
  size =         "7 pages",
  abstract =     "This paper presents our attempt to automatically
                 define feedforward neural networks using genetic
                 programming. Neural networks have been recognized as
                 powerful approximation and classification tools. On the
                 other hand, the genetic programming has been used
                 effectively for the production of intelligent systems,
                 such as the neural networks. In order to reduce the
                 search space and guide the search process we employ
                 grammar restrictions to the genetic programming
                 population individuals. To implement these
                 restrictions, we selected to apply a context-free
                 grammar, such as a BNF grammar. The proposed grammar
                 extends developments of cellular encoding, inherits
                 present advances and manages to express arbitrarily
                 large and connected neural networks. Our implementation
                 uses parameter passing by reference in order to emulate
                 the parallel processing of neural networks into the
                 genetic programming tree individuals. The system is
                 tested in two real-world domains denoting its potential
                 future use.",
}

Genetic Programming entries for Athanasios D Tsakonas Georgios Dounias

Citations