Genetic Network Programming with new genetic operators

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Ye:2010:SMC,
  author =       "Fengming Ye and Shingo Mabu and Lutao Wang and 
                 Kotaro Hirasawa",
  title =        "Genetic Network Programming with new genetic
                 operators",
  booktitle =    "2010 IEEE International Conference on Systems Man and
                 Cybernetics (SMC)",
  year =         "2010",
  month =        "10-13 " # oct,
  pages =        "3346--3353",
  address =      "Istanbul",
  abstract =     "Recently, a new approach named Genetic Network
                 Programming (GNP) has been proposed. GNP can evolve
                 itself and find the optimal solutions. It is based on
                 the ideas of classical evolutionary computation methods
                 such as Genetic Algorithm (GA) and Genetic Programming
                 (GP) and uses the data structure of directed graphs
                 which is the unique feature of GNP. Many studies have
                 demonstrated that GNP can well solve the complex
                 problems in the dynamic environments very efficiently
                 and effectively. As a result, recently, GNP is getting
                 more and more attentions and is being used in many
                 different areas such as data mining, extracting trading
                 rules of stock markets, elevator supervised control
                 systems, etc. Focusing on GNP's distinguished
                 expression ability of the graph structure, this paper
                 proposes an enhanced architecture for the standard GNP
                 in order to improve the performance GNP by using the
                 exploited information extensively during the evolution
                 process of GNP. In the enhanced architecture, we
                 proposed the new genetic operator named Individual
                 Reconstruction which reconstructs and enhances the
                 worst individuals by using the elite information and
                 the crossover and mutation operators of GNP are also
                 modified. In this paper, the proposed architecture has
                 been applied to the tile-world which is an excellent
                 bench mark for evaluating the evolutionary computation
                 architecture. The performance of the new GNP is
                 compared with the conventional GNP. The simulation
                 results show some advantages of the proposed method
                 over the conventional GNPs demonstrating its
                 superiority.",
  keywords =     "genetic algorithms, genetic programming, Ggenetic
                 network programming, NP, Individual Reconstruction,
                 data mining, data structure, directed graphs, elevator
                 supervised control system, evolutionary computation
                 method, genetic operator, stock markets, trading rules
                 extraction, data mining, data structures",
  DOI =          "doi:10.1109/ICSMC.2010.5642337",
  ISSN =         "1062-922X",
  notes =        "Also known as \cite{5642337}",
}

Genetic Programming entries for Fengming Ye Shingo Mabu Lutao Wang Kotaro Hirasawa

Citations