Chaos 21, 037101 (2011); http://dx.doi.org/10.1063/1.3643065 (5 pages)
Introduction to Focus Issue on “Randomness, Structure, and Causality: Measures of Complexity from Theory to Applications”
(Received 26 August 2011; published online 30 September 2011)
We introduce the contributions to this Focus Issue and describe their origin in a recent Santa Fe Institute workshop.
© 2011 American Institute of Physics
Article Outline
- INTRODUCTION
- OVERVIEW OF CONTRIBUTIONS TO THE FOCUS ISSUE
- CLOSING REMARKS
RELATED DATABASES
KEYWORDS and PACS
ARTICLE DATA
Digital Object Identifier
- Entropy, Complexity, and the Physics of Information, edited by W. Zurek, Volume VIII of SFI Studies in the Sciences of Complexity (Addison-Wesley, Reading, MA, 1990).
- A. del Junco and M. Rahe, “Finitary codings and weak Bernoulli partitions,” Proc. AMS 75, 259 (1979). [ISI]
- J. P. Crutchfield and N. H. Packard, “Symbolic dynamics of one-dimensional maps: Entropies, finite precision, and noise,” Int. J. Theor. Phys. 21, 433 (1982). [Inspec] [ISI]
- K.-E. Eriksson and K. Lindgren, “Structural information in self-organizing systems,” Phys. Scr. 35, 388 (1987). [Inspec]
- P. Grassberger, “Toward a quantitative theory of self-generated complexity,” Int. J. Theor. Phys. 25, 907 (1986).
- W. Ebeling, L. Molgedey, J. Kurths, and U. Schwarz, “Entropy, complexity, predictability and data analysis of time series and letter sequences,” in Theory of Disaster, edited by A. Bundle and H.-J. Schellnhuber (Springer Verlag, Berlin, 2000).
- J. P. Crutchfield and D. P. Feldman, “Regularities unseen, randomness observed: Levels of entropy convergence,” Chaos 13(1), 25 (2003)CHAOEH000013000001000025000001. [ISI] [MEDLINE]
- J. P. Crutchfield and K. Young, “Inferring statistical complexity,” Phys. Rev. Let. 63, 105 (1989). [MEDLINE]
- J. P. Crutchfield and D. P. Feldman, “Statistical complexity of simple one-dimensional spin systems,” Phys. Rev. E 55(2), 1239R (1997).
- C. R. Shalizi and J. P. Crutchfield, “Computational mechanics: Pattern and prediction, structure and simplicity,” J. Stat. Phys. 104, 817 (2001).
- C. H. Bennett, “How to define complexity in physics, and why,” in Complexity, Entropy and the Physics of Information, edited by W. H. Zurek, SFI Studies in the Sciences of Complexity, Vol. 7 (Addison-Wesley, Reading, MA, 1990) p. 137.
- M. Li and P. M. B. Vitanyi, An Introduction to Kolmogorov Complexity and its Applications (Springer-Verlag, New York, 1993).
- C. H. Bennett, “Universal computation and physical dynamics,” Physica D 86, 268 (1995). [Inspec] [ISI]
- J. Machta and R. Greenlaw, “The computational complexity of generating random fractals,” J. Stat. Phys. 82, 1299 (1996). [Inspec] [ISI]
- J. Machta, “Complexity, parallel computation and statistical physics,” J. Complex 11(5), 46 (2006).
- G.-M. Murray and S. Lloyd, “Information measures, effective complexity, and total information,” Complexity 2(1), 44 (1996). [Inspec]
- N. Ay, M. Mueller, and A. Szkola, “Effective complexity and its relation to logical depth,” IEEE Trans. Information Theory 56(9), 4593 (2010).
- K. Lindgren and M. G. Norhdal, “Complexity measures and cellular automata,” Complex Syst. 2(4), 409 (1988). [Inspec]
- J. P. Crutchfield, “The calculi of emergence: Computation, dynamics, and induction,” Physica D 5, 11 (1994). [Inspec] [ISI]
- D. P. Feldman and J. P. Crutchfield, Discovering non-critical organization: Statistical mechanical, information theoretic, and computational views of patterns in simple one-dimensional spin systems (Santa Fe Institute Working Paper 98-04-026, 1998).
- J. P. Crutchfield, W. Ditto, and S. Sinha, “Intrinsic and designed computation: Information processing in dynamical systems—Beyond the digital hegemony,” Chaos 20(3), 037101 (2010)CHAOEH000020000003037101000001. [MEDLINE]
- N. H. Packard, J. P. Crutchfield, J. D. Farmer, and R. S. Shaw, “Geometry from a time series,” Phys. Rev. Lett. 45, 712 (1980).
- D. Nerukh, V. Ryabov, and R. C. Glen, “Complex temporal patterns in molecular dynamics: A direct measure of the phase-space exploration by the trajectory at macroscopic time scales,” Phys. Rev. E 77(3), 036225 (2008).
- C.-B. Li, H. Yang, and T. Komatsuzaki, “Multiscale complex network of protein conformational fluctuations in single-molecule time series,” Proc. Natl. Acad. Sci. U.S.A 105, 536 (2008). [MEDLINE]
- A. J. Palmer, C. W. Fairall, and W. A. Brewer, “Complexity in the atmosphere,” IEEE Trans. Geosci. Remote Sens. 38(4), 2056 (2000). [Inspec] [ISI]
- H. Janicke, A. Wiebel, G. Scheuermann, and W. Kollmann, “Multifield visualization using local statistical complexity,” IEEE Trans. Vis. Comput. Graph. 13(6), 1384 (2007).
- J.-S. Yang, W. Kwak, T. Kaizoji, and I.-M. Kim, “Increasing market efficiency in the stock markets,” Eur. Phys. J. B 61(2), 241 (2008).
- N. Ay, J. C. Flack, and D. C. Krakauer, “Robustness and complexity co-constructed in multimodal signalling networks,” Philos. Trans. R. Soc. London, Ser. B 362, 441 (2007). [MEDLINE]
- J. Anders and K. Wiesner, “Increasing complexity with quantum physics,” Chaos 21, 037102 (2011).
- N. Ay, E. Olbrich, N. Bertschinger, and J. Jost, “A geometric approach to complexity,” Chaos 21, 037103 (2011).
- B. Flecker, W. Alford, J. Beggs, P. Williams, and R. Beer, “Partial information decomposition as a spatiotemporal filter,” Chaos 21, 037104 (2011).
- L. Debowski, “Excess entropy in natural language: Present state and perspectives,” Chaos 21, 037105 (2011).
- S. DeDeo, “Effective theories for circuits and automata,” Chaos 21, 037106 (2011).
- C. Ellison, J. Mahoney, R. James, J. P. Crutchfield, and J. Reichardt, “Information Symmetries in Irreversible Processes,” Chaos 21, 037107 (2011).
- J. C. Flack and D. C. Krakauer, “Challenges for complexity measures: A perspective from social dynamics and collective social computation,” Chaos 21, 037108 (2011).
- R. James, C. Ellison, and J. P. Crutchfield, “Anatomy of a bit: Information in a time series observation,” Chaos 21, 037109 (2011).
- D. Krakauer, “Darwinian demons, evolutionary complexity, and information maximization,” Chaos 21, 037110 (2011).
- J. Machta, “Natural complexity, computational complexity and depth,” Chaos 21, 037111 (2011).
- J. Mahoney, C. Ellison, R. James, and J. P. Crutchfield, “How Hidden are Hidden Processes? A Primer on Crypticity and Entropy Convergence,” Chaos 21, 037112 (2011).
- V. Ryabov and D. Nerukh, “Computational mechanics of molecular systems: Quantifying high dimensional dynamics by distribution of Poincare recurrence times,” Chaos 21, 037113 (2011).
- M. Robinson, D. P. Feldman, and S. McKay, “Local entropy and structure in a two-dimensional frustrated system,” Chaos 21, 037114 (2011).
- R. Vilela-Mendes, “Ergodic parameters and dynamical complexity,” Chaos 21, 037115 (2011).
















This Publication
Scitation
SPIN
Google Scholar
PubMed