A virtual creatures model for studies in artificial evolution

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@InProceedings{Miconi:Avc:cec2005,
  author =       "T. Miconi and A. Channon",
  title =        "A virtual creatures model for studies in artificial
                 evolution",
  booktitle =    "Proceedings of the 2005 IEEE Congress on Evolutionary
                 Computation",
  year =         "2005",
  editor =       "David Corne and Zbigniew Michalewicz and Bob McKay and 
                 Gusz Eiben and David Fogel and Carlos Fonseca and 
                 Garrison Greenwood and Gunther Raidl and 
                 Kay Chen Tan and Ali Zalzala",
  pages =        "565--572",
  address =      "Edinburgh, Scotland, UK",
  month =        "2-5 " # sep,
  publisher =    "IEEE Press",
  volume =       "1",
  ISBN =         "0-7803-9363-5",
  URL =          "http://www.channon.net/alastair/papers/cec2005.pdf",
  keywords =     "genetic algorithms, genetic programming, ANN",
  URL =          "http://ieeexplore.ieee.org/servlet/opac?punumber=10417&isvol=1",
  URL =          "http://ieeexplore.ieee.org/servlet/opac?punumber=10417",
  DOI =          "doi:10.1109/CEC.2005.1554733",
  abstract =     "We present the results of our replication of Karl
                 Sims' work on the evolution of artificial creatures in
                 a physically realistic 3D environment. We used standard
                 McCulloch-Pitts neurons instead of a more complex set
                 of ad hoc neurons, which we believe makes our model a
                 more general tool for future experiments in artificial
                 (co-)evolution. We provide a detailed description of
                 our model and freely accessible source code. We
                 describe our results both qualitatively and
                 quantitatively, including an analysis of some evolved
                 neural controllers. To the best of our knowledge, our
                 work is the first replication of Sims' efforts to
                 achieve results comparable to Sims' in efficiency and
                 complexity, with standard neurons and realistic
                 Newtonian physics.",
  notes =        "CEC2005 - A joint meeting of the IEEE, the IEE, and
                 the EPS.",
}

Genetic Programming entries for Thomas Miconi Alastair D Channon

Citations