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How to measure self-generated complexity

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  • Grassberger, Peter

Abstract

In an increasing number of simple dynamical systems, patterns arise which are judged as “complex” in some naive sense. In this talk, quantities are discussed which can serve as measures of this complexity. They are measure-theoretic constructs. In contrast to the Kolmogorov complexity, they are small both for completely ordered and for completely random patterns. Some of the most interesting patterns have indeed zero randomness but infinite complexity in the present sense.

Suggested Citation

  • Grassberger, Peter, 1986. "How to measure self-generated complexity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 140(1), pages 319-325.
    • Handle: RePEc:eee:phsmap:v:140:y:1986:i:1:p:319-325
    DOI: 10.1016/0378-4371(86)90238-4
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    Cited by:

    1. Aksentijevic, A. & Mihailović, D.T. & Kapor, D. & Crvenković, S. & Nikolic-Djorić, E. & Mihailović, A., 2020. "Complementarity of information obtained by Kolmogorov and Aksentijevic–Gibson complexities in the analysis of binary time series," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).
    2. Aleksandar Aksentijevic, 2017. "Randomness: off with its heads (and tails)," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 16(1), pages 1-15, November.

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