Paper Info
Title
Complexity and information: Measuring emergence, self-organization, and homeostasis at multiple scales
Abstract
Concepts used in the scientific study of complex systems have become so widespread that their use and abuse has led to ambiguity and confusion in their meaning. In this article, we use information theory to provide abstract and concise measures of complexity, emergence, self-organization, and homeostasis. The purpose is to clarify the meaning of these concepts with the aid of the proposed formal measures. In a simplified version of the measures (focusing on the information produced by a system), emergence becomes the opposite of self-organization, while complexity represents their balance. Homeostasis can be seen as a measure of the stability of the system. We use computational experiments on random Boolean networks and elementary cellular automata to illustrate our measures at multiple scales. © 2012 Wiley Periodicals, Inc. Complexity, 2012 © 2012 Wiley Periodicals, Inc.
Year
DOI
Venue
2012
10.1002/cplx.21424
Complexity
Keywords
DocType
Volume
multiple scale,elementary cellular automaton,concise measure,random boolean network,wiley periodicals,complex system,inc. complexity,computational experiment,information theory,proposed formal measure,information,complexity,emergence,self organization,homeostasis
Journal
18
Issue
ISSN
Citations 
2
Complexity 18(2):29-44. 2012
38
PageRank 
References 
Authors
2.17
33
2
Name
Order
Citations
PageRank
Carlos Gershenson139242.34
Nelson Fernández2382.17