Inductive Genetic Programming and Superposition of Fitness Landscapes

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Vanio Slavov and Nikolay I. Nikolaev",
  title =        "Inductive Genetic Programming and Superposition of
                 Fitness Landscapes",
  booktitle =    "Genetic Algorithms: Proceedings of the Seventh
                 International Conference",
  year =         "1997",
  editor =       "Thomas Back",
  pages =        "97--104",
  address =      "Michigan State University, East Lansing, MI, USA",
  publisher_address = "San Francisco, CA, USA",
  month =        "19-23 " # jul,
  publisher =    "Morgan Kaufmann",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "1-55860-487-1",
  broken =       "",
  URL =          "",
  URL =          "",
  size =         "8 pages",
  abstract =     "This paper presents an approach to improving the
                 performance of evolutionary algorithms. The
                 evolutionary search effort is distributed among
                 cooperating subpopulations that correspond to the
                 substructures of the fitness landscape. The idea is to
                 create such subpopulations that flow easily on the
                 simple substructures of the complex fitness landscape
                 structure. We claim that the search on a complex
                 fitness landscape is facilitated if properly integrated
                 with search on its simple components. This evolutionary
                 structured search is applied for solving hard inductive
                 learning tasks. The performance observed while inducing
                 regular grammars from sets of boolean strings
                 demonstrated that the approach mitigates the search
  notes =        "ICGA-97

                 Except for the reversal of the order of the authors
                 appears to be almost identical to the published

Genetic Programming entries for Vanio Slavov Nikolay Nikolaev