Developmental Plasticity in Cartesian Genetic Programming based Neural Networks

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Maryam Mahsal Khan and Gul Muhammad Khan and 
                 Julian F. Miller",
  title =        "Developmental Plasticity in Cartesian Genetic
                 Programming based Neural Networks",
  booktitle =    "Proceedings of the 8th International Conference on
                 Informatics in Control, Automation and Robotics (ICINCO
  year =         "2011",
  editor =       "Jean-Louis Ferrier and Alain Bernard and 
                 Oleg Yu. Gusikhin and Kurosh Madani",
  volume =       "1",
  pages =        "449--458",
  address =      "Noordwijkerhout, The Netherlands,",
  month =        "28 - 31 " # jul,
  publisher =    "SciTePress",
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming",
  isbn13 =       "978-989-8425-74-4",
  URL =          "",
  size =         "11 pages",
  abstract =     "This work presents a method for exploiting
                 developmental plasticity in Artificial Neural Networks
                 using Cartesian Genetic Programming. This is inspired
                 by developmental plasticity that exists in the
                 biological brain allowing it to adapt to a changing
                 environment. The network architecture used is that of a
                 static Cartesian Genetic Programming ANN, which has
                 recently been introduced. The network is plastic in
                 terms of its dynamic architecture, connectivity,
                 weights and functionality that can change in response
                 to the environmental signals. The dynamic capabilities
                 of the algorithm are tested on a standard benchmark
                 linear/non-linear control problems (i.e.
  bibdate =      "2012-05-02",
  bibsource =    "DBLP,

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