Genetic Programming with Scale-Free Dynamics

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

  author =       "Hitoshi Araseki",
  title =        "Genetic Programming with Scale-Free Dynamics",
  booktitle =    "EVOLVE - A Bridge between Probability, Set Oriented
                 Numerics, and Evolutionary Computation IV",
  year =         "2013",
  editor =       "Michael Emmerich and Andre Deutz and 
                 Oliver Schuetze and Thomas Baeck and Emilia Tantar and 
                 Alexandru-Adrian and Pierre {Del Moral} and Pierrick Legrand and 
                 Pascal Bouvry and Carlos A. Coello",
  volume =       "227",
  series =       "Advances in Intelligent Systems and Computing",
  pages =        "277--291",
  address =      "Leiden, Holland",
  month =        jul # " 10-13",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-319-01127-1",
  DOI =          "doi:10.1007/978-3-319-01128-8_18",
  abstract =     "This paper describe a new selection method, named
                 SFSwT (Scale-Free Selection method with Tournament
                 mechanism) which is based on a scale-free network
                 study. A scale-free selection model was chosen in order
                 to generate a scale-free structure. The proposed model
                 reduces computational complexity and improves
                 computational performance compared with a previous
                 version of the model. Experimental results with various
                 benchmark problems show that performance of the SFSwT
                 is higher than with other selection methods. In various
                 fields, scale-free structures are closely related to
                 evolutionary computation. Further, it was found through
                 the experiments that the distribution of node
                 connectivity could be used as an index of search

Genetic Programming entries for Hitoshi Araseki