Multiple Interacting Programs: A Representation for Evolving Complex Behaviors

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  author =       "Peter J. Angeline",
  title =        "Multiple Interacting Programs: A Representation for
                 Evolving Complex Behaviors",
  journal =      "Cybernetics and Systems",
  year =         "1998",
  volume =       "29",
  number =       "8",
  pages =        "779--803",
  month =        nov,
  keywords =     "genetic algorithms, genetic programming, mips",
  ISSN =         "0196-9722",
  URL =          "",
  URL =          "",
  DOI =          "doi:10.1080/019697298125407",
  size =         "25 pages",
  abstract =     "This paper defines a representation for expressing
                 complex behaviors, called multiple interacting programs
                 (MIPs), and describes an evolutionary method for
                 evolving solutions to difficult problems expressed as
                 MIPs structures. The MIPs representation is a
                 generalization of neural network architectures that can
                 model any type of dynamic system. The evolutionary
                 training method described is based on an evolutionary
                 program originally used to evolve the architecture and
                 weights of recurrent neural networks. Example
                 experiments demonstrate the training method s ability
                 to evolve appropriate MIPs solutions for difficult
                 problems. An analysis of the evolved solutions shows
                 their dynamics to be interesting and non-trivial.",
  notes =        "Sun spots, Santa Fe trail Artifical Ant, 5-bit
                 reverser, Tree, ANN",

Genetic Programming entries for Peter John Angeline