Obtaining Repetitive Actions for Genetic Programming with Multiple Trees

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@Article{Ito:2016:PCS,
  author =       "Takashi Ito and Kenichi Takahashi and 
                 Michimasa Inaba",
  title =        "Obtaining Repetitive Actions for Genetic Programming
                 with Multiple Trees",
  journal =      "Procedia Computer Science",
  volume =       "96",
  pages =        "120--128",
  year =         "2016",
  note =         "Knowledge-Based and Intelligent Information and
                 Engineering Systems: Proceedings of the 20th
                 International Conference KES-2016",
  ISSN =         "1877-0509",
  DOI =          "doi:10.1016/j.procs.2016.08.111",
  URL =          "http://www.sciencedirect.com/science/article/pii/S1877050916319123",
  abstract =     "This paper proposes a method to improve genetic
                 programming with multiple trees (GPCN). An individual
                 in GPCN comprises multiple trees, and each tree has a
                 number P that indicates the number of repetitive
                 actions based on the tree. In previous work, a method
                 for updating the number P has been proposed to obtain P
                 suitable to the tree in evolution. However, in the
                 method efficiency becomes worse as the range of P
                 becomes wider. In order to solve the problem, in this
                 study, two methods are proposed: inheriting the number
                 P of a tree from an excellent individual and using
                 mutation for preventing the number P from being into a
                 local optimum. Additionally, a method to eliminate
                 trees consisting of a single terminal node is
                 proposed.",
  keywords =     "genetic algorithms, genetic programming, autonomous
                 agent, garbage collection problem, evolutionary
                 learning, multiple trees.",
}

Genetic Programming entries for Takashi Ito Ken-ichi Takahashi Michimasa Inaba

Citations