Evolution of neural networks using Cartesian Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4020

  author =       "Maryam Mahsal Khan and Gul Muhammad Khan and 
                 Julian F. Miller",
  title =        "Evolution of neural networks using Cartesian Genetic
  booktitle =    "IEEE Congress on Evolutionary Computation (CEC 2010)",
  year =         "2010",
  address =      "Barcelona, Spain",
  month =        "18-23 " # jul,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 Genetic Programming",
  isbn13 =       "978-1-4244-6910-9",
  abstract =     "A novel Neuroevolutionary technique based on Cartesian
                 Genetic Programming is proposed (CGPANN). ANNs are
                 encoded and evolved using a representation adapted from
                 the CGP. We have tested the new approach on the single
                 pole balancing problem. Results show that CGPANN
                 evolves solutions faster and of higher quality than the
                 most powerful algorithms of Neuroevolution in the
  DOI =          "doi:10.1109/CEC.2010.5586547",
  notes =        "WCCI 2010. Also known as \cite{5586547}",

Genetic Programming entries for Maryam Mahsal Khan Gul Muhammad Khan Julian F Miller