Promoting Generalization of Learned Behaviours in Genetic Programming   [GP]

by

Kuscu, I.

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Info: Fifth International Conference on Parallel Problem Solving from Nature (Conference proceedings), 1998, p. 491-500
Keywords:genetic algorithms, genetic programming
Abstract:
Recently, growing numbers of research concentrate on robustness of the programs evolved using GP. While some of the researchers report on the brittleness of the solutions evolved, some others proposed methods of promoting robustness. It is important that these methods are not ad hoc and specific for a certain experimental setup. In this research, brittleness of solutions found for the artificial ant problem [AA] [AP] is reported, and a new method promoting generalization of the solution is presented.
Notes:
PPSN-V
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BibTex:
@InProceedings{kuscu:1998:pglbGP,
  author =       "Ibrahim Kuscu",
  title =        "Promoting Generalization of Learned Behaviours in
                 Genetic Programming",
  booktitle =    "Fifth International Conference on Parallel Problem
                 Solving from Nature",
  year =         "1998",
  editor =       "Agoston E. Eiben and Thomas Back and Marc Schoenauer
                 and Hans-Paul Schwefel",
  volume =       "1498",
  series =       "LNCS",
  pages =        "491--500",
  address =      "Amsterdam",
  publisher_address = "Berlin",
  month =        "27-30 " # sep,
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-65078-4",
  abstract =     "Recently, growing numbers of research concentrate on
                 robustness of the programs evolved using GP. While some
                 of the researchers report on the brittleness of the
                 solutions evolved, some others proposed methods of
                 promoting robustness. It is important that these
                 methods are not ad hoc and specific for a certain
                 experimental setup. In this research, brittleness of
                 solutions found for the artificial ant problem is
                 reported, and a new method promoting generalization of
                 the solution is presented.",
  notes =        "PPSN-V",
}