Untidy Evolution: Evolving Messy Gates for Fault Tolerance

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@InProceedings{ICES2001,
  author =       "Julian F. Miller and Morten Hartmann",
  title =        "Untidy Evolution: Evolving Messy Gates for Fault
                 Tolerance",
  booktitle =    "Evolvable Systems: From Biology to Hardware: 4th
                 International Conference, ICES 2001",
  year =         "2001",
  editor =       "Yong Liu and Kiyoshi Tanaka and Masaya Iwata and 
                 Tetsuya Higuchi and Moritoshi Yasunaga",
  volume =       "2210",
  series =       "LNCS",
  pages =        "14--25",
  address =      "Tokyo, Japan",
  month =        "3-5 " # oct,
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-42671-X",
  ISSN =         "0302-9743",
  URL =          "http://www.elec.york.ac.uk/intsys/users/jfm7/ices2001.pdf",
  URL =          "http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2210&spage=14",
  abstract =     "The exploitation of the physical characteristics has
                 already been demonstrated in the intrinsic evolution of
                 electronic circuits. This paper is an initial attempt
                 at creating a world in which {"}physics{"} can be
                 exploited in simulation. As a starting point we
                 investigate a model of gate-like components with added
                 noise. We refer to this as a kind of messiness . The
                 principal idea behind these messy gates is that
                 artificial evolution makes a virtue of the untidiness.
                 We are ultimately trying to study the question: What
                 kind of components should we use in artificial
                 evolution? Several experiments are described that show
                 that the messy circuits have a natural robustness to
                 noise, as well as an implicit fault-tolerance. In
                 addition, it was relatively easy for evolution to
                 generate novel circuits that were surprisingly
                 efficient.",
}

Genetic Programming entries for Julian F Miller Morten Hartmann

Citations