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Building Efficient Computational Cellular Automata Models Of Complex Systems: Background, Applications, Results, Software, And Pathologies

Author

Listed:
  • JIŘÍ KROC

    (Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Alej Svobody 76, Pilsen 323 00, The Czech Republic)

  • FRANCISCO JIMÉNEZ-MORALES

    (#x2020;Department of Condensed Matter Physics, University of Seville, Avda. Reina Mercedes, S/N, Seville 41012, Spain)

  • J. L. GUISADO

    (#x2021;Department of Computer Architecture and Technology, University of Seville, Avda. Reina Mercedes, S/N, Seville 41012, Spain)

  • MARÍA CARMEN LEMOS

    (#x2020;Department of Condensed Matter Physics, University of Seville, Avda. Reina Mercedes, S/N, Seville 41012, Spain)

  • JAKUB TKÁČ

    (#xA7;Faculty of Electrical Engineering, Czech Technical University, Technická 2, Prague 166 27, The Czech Republic)

Abstract

Cellular automaton models of complex systems (CSs) are gaining greater popularity; simultaneously, they have proven the capability to solve real scientific and engineering applications. To enable everybody a quick penetration into the core of this type of modeling, three real applications of cellular automaton models, including selected open source software codes, are studied: laser dynamics, dynamic recrystallization (DRX) and surface catalytic reactions.The paper is written in a way that it enables any researcher to reach the cutting edge knowledge of the design principles of cellular automata (CA) models of the observed phenomena in any scientific field. The whole sequence of design steps is demonstrated: definition of the model using topology and local (transition) rule of a cellular automaton, achieved results, comparison to real experiments, calibration, pathological observations, flow diagrams, software, and discussions. Additionally, the whole paper demonstrates the extreme expressiveness and flexibility of massively parallel computational approaches compared to other computational approaches. The paper consists of the introductory parts that are explaining CSs, self-organization and emergence, entropy, and CA. This allows readers to realize that there is a large variability in definitions and solutions of this class of models.

Suggested Citation

  • Jiří Kroc & Francisco Jiménez-Morales & J. L. Guisado & María Carmen Lemos & Jakub Tkáč, 2019. "Building Efficient Computational Cellular Automata Models Of Complex Systems: Background, Applications, Results, Software, And Pathologies," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-38, August.
    • Handle: RePEc:wsi:acsxxx:v:22:y:2019:i:05:n:s0219525919500139
    DOI: 10.1142/S0219525919500139
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    References listed on IDEAS

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    1. Tang, Tie-Qiao & Luo, Xiao-Feng & Zhang, Jian & Chen, Liang, 2018. "Modeling electric bicycle’s lane-changing and retrograde behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1377-1386.
    2. J. L. Guisado & F. Jiménez-Morales & F. Fernández De Vega, 2007. "Cellular Automata And Cluster Computing: An Application To The Simulation Of Laser Dynamics," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 10(supp0), pages 167-190.
    3. Burkhead, Emily & Hawkins, Jane, 2015. "A cellular automata model of Ebola virus dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 424-435.
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