The Art of Nature: Evolving Mechanisms of Development for Self- Organization and Differentiation

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

@InProceedings{kumar:2005:CEC,
  author =       "Sanjeev Kumar",
  title =        "The Art of Nature: Evolving Mechanisms of Development
                 for Self- Organization and Differentiation",
  booktitle =    "Proceedings of the 2005 IEEE Congress on Evolutionary
                 Computation",
  year =         "2005",
  editor =       "David Corne and Zbigniew Michalewicz and 
                 Marco Dorigo and Gusz Eiben and David Fogel and Carlos Fonseca and 
                 Garrison Greenwood and Tan Kay Chen and 
                 Guenther Raidl and Ali Zalzala and Simon Lucas and Ben Paechter and 
                 Jennifier Willies and Juan J. Merelo Guervos and 
                 Eugene Eberbach and Bob McKay and Alastair Channon and 
                 Ashutosh Tiwari and L. Gwenn Volkert and 
                 Dan Ashlock and Marc Schoenauer",
  volume =       "1",
  pages =        "551--558",
  address =      "Edinburgh, UK",
  publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
                 08855-1331, USA",
  month =        "2-5 " # sep,
  organisation = "IEEE Computational Intelligence Society, Institution
                 of Electrical Engineers (IEE), Evolutionary Programming
                 Society (EPS)",
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-7803-9363-5",
  DOI =          "doi:10.1109/CEC.2005.1554731",
  abstract =     "Recently, researchers have recognised the benefits of
                 learning from biological development in order to
                 engineer self-organising solutions to problems. This
                 paper explores the application of the developmental
                 metaphor to the problem of controlling single and
                 multicellular development. In this paper, a summary of
                 experiments performed using a multicellular test-bed
                 model of biological development, the Evolutionary
                 Developmental System (EDS), is presented. The EDS is
                 shown to successfully evolve genetic regulatory
                 networks that specify and control the behaviour of
                 single cells and the construction of 3D multicellular
                 geometric morphologies to explore self organisation and
                 analogues of phenomena akin to biological cell
                 differentiation in multicellular development.",
  notes =        "CEC2005 - A joint meeting of the IEEE, the IEE, and
                 the EPS.",
}

Genetic Programming entries for Sanjeev Kumar

Citations