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An entropy based measure for comparing distributions of complexity
| Content Provider | Semantic Scholar |
|---|---|
| Author | Rajaram, Rajeev Castellani, Brian |
| Copyright Year | 2016 |
| 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. |
| Starting Page | 35 |
| Ending Page | 43 |
| Page Count | 9 |
| File Format | PDF HTM / HTML |
| DOI | 10.1016/j.physa.2016.02.007 |
| Volume Number | 453 |
| Alternate Webpage(s) | http://www.personal.kent.edu/~bcastel3/EntropyPhysicaA2016.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
