Solving the even-n-parity problems using Best SubTree Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{DBLP:conf/ahs/MunteanDO07,
  author =       "Oana Muntean and Laura Diosan and Mihai Oltean",
  title =        "Solving the even-n-parity problems using Best SubTree
                 Genetic Programming",
  booktitle =    "Second NASA/ESA Conference on Adaptive Hardware and
                 Systems (AHS 2007)",
  year =         "2007",
  bibsource =    "DBLP, http://dblp.uni-trier.de",
  pages =        "511--518",
  address =      "Edinburgh",
  month =        aug # " 5-8",
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming, digital
                 circuits, logic design, trees (mathematics), digital
                 circuit design, even-n-parity problem, subtree genetic
                 programming",
  DOI =          "doi:10.1109/AHS.2007.99",
  size =         "8 pages",
  abstract =     "Best subtree genetic programming (BSTGP) is a special
                 genetic programming (GP) variant whose aim is to offer
                 more possibilities, for selecting the solution,
                 compared to standard GP. In the case of BSTGP the best
                 subtree is chosen for proving the solution. This is
                 different from standard GP where the solution was given
                 by the entire tree. In this paper we apply BSTGP for
                 designing digital circuits for the even-n-parity
                 problem. Numerical results show that BSTGP can improve
                 GP search in terms of success rate and computational
                 effort.",
}

Genetic Programming entries for Oana Muntean Laura Diosan Mihai Oltean

Citations