In Search of Intelligent Genes: The Cartesian Genetic Programming Computational Neuron (CGPCN)

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

  author =       "Gul Muhammad Khan and Julian F. Miller and 
                 David Halliday",
  title =        "In Search of Intelligent Genes: The Cartesian Genetic
                 Programming Computational Neuron (CGPCN)",
  booktitle =    "2009 IEEE Congress on Evolutionary Computation",
  year =         "2009",
  editor =       "Andy Tyrrell",
  pages =        "574--581",
  address =      "Trondheim, Norway",
  month =        "18-21 " # may,
  organization = "IEEE Computational Intelligence Society",
  publisher =    "IEEE Press",
  isbn13 =       "978-1-4244-2959-2",
  file =         "P138.pdf",
  DOI =          "doi:10.1109/CEC.2009.4982997",
  abstract =     "Biological neurons are extremely complex cells whose
                 morphology grows and changes in response to the
                 external environment. Yet, artificial neural networks
                 (ANNs) have represented neurons as simple computational
                 devices. It has been evident for a long time that ANNs
                 have learning abilities that are insignificant compared
                 with some of the simplest biological brains. We argue
                 that we understand enough neuroscience to create much
                 more sophisticated models. In this paper, we report on
                 our attempts to do this.We identify and evolve seven
                 programs that together represents a neuron which grows
                 post evolution into a complete 'neurological' system.
                 The network that occurs by running the programs has a
                 highly dynamic morphology in which neurons grow, and
                 die, and neurite branches together with synaptic
                 connections form and change. We have evaluated the
                 capability of these networks for playing the game of
                 checkers. Our method has no board evaluation function,
                 no explicit learning rules and no human expertise at
                 playing checkers is used. The learning abilities of
                 these networks are encoded at a genetic level rather
                 than at the phenotype level of neural connections.",
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming",
  notes =        "CEC 2009 - A joint meeting of the IEEE, the EPS and
                 the IET. IEEE Catalog Number: CFP09ICE-CDR",

Genetic Programming entries for Gul Muhammad Khan Julian F Miller David M Halliday