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Cell state change dynamics in cellular automata

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Abstract

Cellular automata are discrete dynamical systems having the ability to generate highly complex behaviour starting from a simple initial configuration and set of update rules. The discovery of rules exhibiting a high degree of global self-organization is of major importance in the study and understanding of complex systems. This task is not easily achieved since coordinated global information processing must rise from the interactions of simple components with local information and communication. In this paper, a fast supporting heuristic of linear complexity is proposed to encourage the development of rules characterized by increased dynamics with regard to cell state changes. This heuristic is integrated in an evolutionary approach to the density classification task. Computational experiments emphasize the ability of the proposed approach to facilitate an efficient exploration of the search space leading to the discovery of complex rules situated beyond the simple block-expanding rules.

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Acknowledgments

This research is supported by Grant PN II TE 320, ”Emergence, auto-organization and evolution: New computational models in the study of complex systems”, funded by CNCS Romania. David Iclănzan acknowledges the financial support of the Sectoral Operational Program for Human Resources Development 2007–2013, co-financed by the European Social Fund, within the project POSDRU 89/1.5/S/60189 with the title ”Postdoctoral Programs for Sustainable Development in a Knowledge Based Society” and the support of Sapientia Institute for Research Programs (KPI).

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Authors and Affiliations

  1. Department of Electrical Engineering, Sapientia Hungarian University of Transylvania, CP 4, OP 9, 540485 , Tg-Mureş, Romania

    David Iclănzan

  2. Department of Computer Science, Babeş-Bolyai University, Kogălniceanu, 1, 400084 , Cluj-Napoca, Romania

    Anca Gog & Camelia Chira

Authors
  1. David Iclănzan
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  2. Anca Gog
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  3. Camelia Chira
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Correspondence to Camelia Chira.

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Iclănzan, D., Gog, A. & Chira, C. Cell state change dynamics in cellular automata. Memetic Comp. 5, 131–139 (2013). https://doi.org/10.1007/s12293-012-0093-z

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