The Convergence Mechanism and Strategies for Non-Elitist Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3949

@InProceedings{Ni:2013:iccsee,
  author =       "He Ni and Bo Yu and Fanming Zeng and Fengrui Sun",
  title =        "The Convergence Mechanism and Strategies for
                 Non-Elitist Genetic Programming",
  booktitle =    "Proceedings of the 2nd International Conference on
                 Computer Science and Electronics Engineering",
  year =         "2013",
  series =       "Advances in Intelligent Systems Research",
  publisher =    "Atlantis Press",
  keywords =     "genetic algorithms, genetic programming, non-elitist
                 genetic programming, convergence mechanism, convergence
                 strategy, algorithmic pause time",
  isbn13 =       "978-90-78677-61-1",
  ISSN =         "1951-6851",
  bibsource =    "OAI-PMH server at citeseerx.ist.psu.edu",
  language =     "en",
  oai =          "oai:CiteSeerX.psu:10.1.1.1001.3462",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1001.3462",
  URL =          "http://atlantis-press.com/php/download_paper.php?id%3D5071",
  URL =          "http://www.atlantis-press.com/proceedings/iccsee-13/5071",
  size =         "8 pages",
  abstract =     "Genetic programming is an evolutionary algorithm that
                 proposed to solve the automatic computer program design
                 problem by J.R.Koza in the 1990s. It has good
                 universality and intelligence, and has been widely
                 applied in the field of computer engineering. But
                 genetic programming is essentially a stochastic
                 optimisation algorithm, lack theoretic basis on the
                 convergence of algorithm, which limit the scope of its
                 application in some extent. The convergence mechanism
                 of non-elitist genetic programming was studied in this
                 paper. A recursive estimation of the probability of
                 population contains satisfactory solution with the
                 evolution algebra was established by the analysis of
                 operators characteristic parameters, then a sufficient
                 condition of population converge in probability was
                 derived from this estimation, and thereby some
                 operational convergence strategies for many common
                 evolution modes were provided.",
  notes =        "ICCSEE-13

                 ... permits non-commercial use, distribution and
                 reproduction in any medium, provided the original work
                 is properly cited",
}

Genetic Programming entries for He Ni Bo Yu Fanming Zeng Fengrui Sun

Citations