Next Article in Journal
Top-Down Causation and the Rise of Information in the Emergence of Life
Previous Article in Journal
The Logic of the Physics of Information
Article Menu

Export Article

Open AccessArticle
Information 2014, 5(3), 404-423; doi:10.3390/info5030404

Complexity and Dynamical Depth

Department of Anthropology, 232 Kroeber, University of California, Berkeley, CA 94720, USA
Institute for Philosophy, Literature, and History of Science and Technology, Technical University of Berlin, Strasse des 17. Juni 135, 10623 Berlin, Germany
Author to whom correspondence should be addressed.
Received: 10 June 2014 / Accepted: 30 June 2014 / Published: 14 July 2014
(This article belongs to the Section Information Theory and Methodology)
View Full-Text   |   Download PDF [2094 KB, uploaded 14 July 2014]   |  


We argue that a critical difference distinguishing machines from organisms and computers from brains is not complexity in a structural sense, but a difference in dynamical organization that is not well accounted for by current complexity measures. We propose a measure of the complexity of a system that is largely orthogonal to computational, information theoretic, or thermodynamic conceptions of structural complexity. What we call a system’s dynamical depth is a separate dimension of system complexity that measures the degree to which it exhibits discrete levels of nonlinear dynamical organization in which successive levels are distinguished by local entropy reduction and constraint generation. A system with greater dynamical depth than another consists of a greater number of such nested dynamical levels. Thus, a mechanical or linear thermodynamic system has less dynamical depth than an inorganic self-organized system, which has less dynamical depth than a living system. Including an assessment of dynamical depth can provide a more precise and systematic account of the fundamental difference between inorganic systems (low dynamical depth) and living systems (high dynamical depth), irrespective of the number of their parts and the causal relations between them. View Full-Text
Keywords: complexity; dynamical system; self-organization; machine; organism; teleodynamics; morphodynamics; non-linear; computation; information complexity; dynamical system; self-organization; machine; organism; teleodynamics; morphodynamics; non-linear; computation; information

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Deacon, T.; Koutroufinis, S. Complexity and Dynamical Depth. Information 2014, 5, 404-423.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Information EISSN 2078-2489 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top