A Review Of Methods For Encoding Neural Network Topologies In Evolutionary Computation

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

  author =       "Jozef Fekiac and Ivan Zelinka and Juan C. Burguillo",
  title =        "A Review Of Methods For Encoding Neural Network
                 Topologies In Evolutionary Computation",
  booktitle =    "25th European Conference on Modelling and Simulation,
                 ECMS 2011",
  year =         "2011",
  editor =       "Tadeusz Burczynski and Joanna Kolodziej and 
                 Aleksander Byrski and Marco Carvalho",
  pages =        "410--416",
  address =      "Krakow, Poland",
  month =        jun # " 7-10",
  publisher =    "European Council for Modeling and Simulation",
  keywords =     "genetic algorithms, genetic programming, artificial
                 neural network, automata network, evolutionary
                 computation, network encoding, graph grammar",
  timestamp =    "Tue, 14 Jan 2014 17:49:51 +0100",
  biburl =       "http://dblp2.uni-trier.de/rec/bib/conf/ecms/FekiacZB11",
  bibsource =    "dblp computer science bibliography, http://dblp.org",
  isbn13 =       "978-0-9564944-2-9",
  annote =       "The Pennsylvania State University CiteSeerX Archives",
  bibsource =    "OAI-PMH server at citeseerx.ist.psu.edu",
  language =     "en",
  oai =          "oai:CiteSeerX.psu:",
  rights =       "Metadata may be used without restrictions as long as
                 the oai identifier remains attached to it.",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=",
  URL =          "http://www.scs-europe.net/conf/ecms2011/ecms2011
                 accepted papers/is_ECMS_0081.pdf",
  URL =          "http://www.scs-europe.net/dlib/2011/2011-0410.htm",
  DOI =          "doi:10.7148/2011-0410-0416",
  size =         "7 pages",
  abstract =     "This paper describes various methods used to encode
                 artificial neural networks to chromosomes to be used in
                 evolutionary computation. The target of this review is
                 to cover the main techniques of network encoding and
                 make it easier to choose one when implementing a custom
                 evolutionary algorithm for finding the network
                 topology. Most of the encoding methods are mentioned in
                 the context of neural networks; however all of them
                 could be generalised to automata networks or even
                 oriented graphs. We present direct and indirect
                 encoding methods, and given examples of their
                 genotypes. We also describe the possibilities of
                 applying genetic operators of mutation and crossover to
                 genotypes encoded by these methods. Also, the
                 dependencies of using special evolutionary algorithms
                 with some of the encodings were considered.",

Genetic Programming entries for Jozef Fekiac Ivan Zelinka Juan C Burguillo