Dynamic Systems Modelling with Evolving Cellular Automata

  • A. Dobnikar
  • A. Likar
  • S. Vavpotič
Conference paper


Dynamic systems modelling with evolving cellular automata is described in this paper. The basic idea is to use stochastic cellular automata together with local evolving algorithms in order to model dynamic systems representing certain physical phenomena and on the other hand to search for the optimal local parameters that enable the close fit of the model processing with the actual sequence of the phenomena. With the help of a case study on the problem of the spread of forest fires, we show the value of the approach.


Cellular Automaton Local Parameter Cellular Automaton Learning Sequence Fire Spread 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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    E. Sanchez, M. Tomassini, Towards Evolvable Hardware, Springer, 1996Google Scholar

Copyright information

© Springer-Verlag Wien 1999

Authors and Affiliations

  • A. Dobnikar
    • 1
  • A. Likar
    • 2
  • S. Vavpotič
    • 1
  1. 1.Faculty of Computer and Information ScienceUniversity of LjubljanaLjubljanaSlovenia
  2. 2.Faculty of Mathematics and PhysicsUniversity of LjubljanaLjubljanaSlovenia

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