An entropy based measure for comparing distributions of complexity

R. Rajaram and B. Castellani

Physica A: Statistical Mechanics and its Applications, 2016, vol. 453, issue C, 35-43

Abstract: 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 pi, 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 entropyCc — 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–Cc 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.

Keywords: Probability distributions; Complex systems; Shannon entropy; Measures of complexity (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:453:y:2016:i:c:p:35-43

DOI: 10.1016/j.physa.2016.02.007

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