Evaluation of dynamic behavior forecasting parameters in the process of transition rule induction of unidimensional cellular automata

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@Article{Weinert20106,
  author =       "Wagner Rodrigo Weinert and Heitor Silverio Lopes",
  title =        "Evaluation of dynamic behavior forecasting parameters
                 in the process of transition rule induction of
                 unidimensional cellular automata",
  journal =      "Biosystems",
  volume =       "99",
  number =       "1",
  pages =        "6--16",
  year =         "2010",
  ISSN =         "0303-2647",
  DOI =          "doi:10.1016/j.biosystems.2009.08.002",
  URL =          "http://www.sciencedirect.com/science/article/B6T2K-4X0XFDD-1/2/0604807ff3e25dde5b1b6902b792e157",
  keywords =     "genetic algorithms, genetic programming, Cellular
                 automata, Dynamic behavior forecasting parameters,
                 Dynamic systems, Evolutionary computation",
  abstract =     "The simulation of the dynamics of a cellular systems
                 based on cellular automata (CA) can be computationally
                 expensive. This is particularly true when such
                 simulation is part of a procedure of rule induction to
                 find suitable transition rules for the CA. Several
                 efforts have been described in the literature to make
                 this problem more treatable. This work presents a study
                 about the efficiency of dynamic behaviour forecasting
                 parameters (DBFPs) used for the induction of transition
                 rules of CA for a specific problem: the classification
                 by the majority rule. A total of 8 DBFPs were analysed
                 for the 31 best-performing rules found in the
                 literature. Some of these DBFPs were highly correlated
                 each other, meaning they yield the same information.
                 Also, most rules presented values of the DBFPs very
                 close each other. An evolutionary algorithm, based on
                 gene expression programming, was developed for finding
                 transition rules according a given preestablished
                 behavior. The simulation of the dynamic behavior of the
                 CA is not used to evaluate candidate transition rules.
                 Instead, the average values for the DBFPs were used as
                 reference. Experiments were done using the DBFPs
                 separately and together. In both cases, the best
                 induced transition rules were not acceptable solutions
                 for the desired behavior of the CA. We conclude that,
                 although the DBFPs represent interesting aspects of the
                 dynamic behavior of CAs, the transition rule induction
                 process still requires the simulation of the dynamics
                 and cannot rely only on the DBFPs.",
}

Genetic Programming entries for Wagner R Weinert Heitor Silverio Lopes

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