4.6 Article

An entropy based measure for comparing distributions of complexity

Journal

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.physa.2016.02.007

Keywords

Probability distributions; Complex systems; Shannon entropy; Measures of complexity

Funding

  1. ESRC [ES/L00092X/1] Funding Source: UKRI
  2. Economic and Social Research Council [ES/L00092X/1] Funding Source: researchfish

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This paper is part of a series addressing the empirical/statistical distribution of the diversity of complexity within and amongst complex systems. Here, we consider the problem of measuring the diversity of complexity in a system, given its ordered range of complexity types i and their probability of occurrence p(i), with the understanding that larger values of i mean a higher degree of complexity. To address this problem, we introduce a new complexity measure called case-based entropy C-c - a modification of the Shannon-Wiener entropy measure H. The utility of this measure is that, unlike current complexity measures - which focus on the macroscopic complexity of a single system - C-c can be used to empirically identify and measure the distribution of the diversity of complexity within and across multiple natural and human-made systems, as well as the diversity contribution of complexity of any part of a system, relative to the total range of ordered complexity types. (C) 2016 Elsevier B.V. All rights reserved.

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