The DOI matches its Crossref record; 149 of the 152 references it cites were found in a registry or an index, and 1 are not checked yet.
Computational Mechanics: Pattern and Prediction, Structure and Simplicity
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“These can be abstract (e.g. Turing machines (Delahaye and Zenil, 2007, 2012), ϵ -machines (Shalizi and Crutchfield, 2001; G¨ ornerup and Crutchfield, 2008)), biological (ecosystems, organisms), economic, social or technological (Helbing, 2011).”
From Information Measures of Complexity, Emergence, Self-organization, Homeostasis, and Autopoiesis (2013) · cites this paper as Shalizi and Crutchfield, 2001
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Citations
Cites
A Mathematical Theory of Communication
Shannon, C. E. (1948) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1948.tb01338.x · Cited by 88,486
A Mathematical Theory of Communication
Shannon, C. E. (1948) · The MIT Press eBooks · doi:10.1002/j.1538-7305.1948.tb00917.x · Cited by 50,201
The Nature of Statistical Learning Theory
Vapnik, V. (2000) · Statistics for Engineering and Information Science · doi:10.1007/978-1-4757-3264-1 · Cited by 46,387
The Nature of Statistical Learning Theory
Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138
Elements of Information Theory
Cover, T. M., & Thomas, J. A. (2001) · Wiley eBooks · doi:10.1002/0471200611 · Cited by 37,139
Causality: Models, Reasoning, and Inference
Pearl, J. (2009) · doi:10.1017/cbo9780511803161 · Cited by 11,653
Introduction to automata theory, languages and computation
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Takens, F. (1981) · Lecture Notes in Mathematics · doi:10.1007/bfb0091924 · Cited by 10,459
The Mathematical Theory of Communication
Shannon, C. E., Weaver, W., & Wiener, N. (1950) · Physics Today · doi:10.1063/1.3067010 · Cited by 9,882
Doob, J. L., & Doob, J. L. (1953) · CERN Document Server (European Organization for Nuclear Research) · Cited by 9,053
Research works printed but not linked: 11
- J. P. Crutchfield and K. Young, Computation at the onset of chaos, In Zurek et al.,(137) pages 223–269.
- J. P. Crutchfield, Semantics and thermodynamics, In Nonlinear Modeling and Forecasting, M. Casdagli and S. Eubank, eds., volume 12 of Santa Fe Institute Studies in the Sciences of Complexity, pages 317–359 (Addison-Wesley, Reading, Massachusetts, 1992).
- A. N. Whitehead and B. Russell, Principia Mathematica, 2nd ed. (Cambridge University Press, Cambridge, England), pp. 1925–27.
- J. Rhodes, Applications of Automata Theory and Algebra via the Mathematical Theory of Complexity to Biology, Physics, Psychology, Philosophy, Games, and Codes (University of California, Berkeley, California, 1971).
- C. H. Bennett, How to define complexity in physics, and why, In Zurek et al.,(137) pages 137–148.
- M. Koppel, Complexity, depth, and sophistication, Complex Systems 1:1087–1091 (1987).
- M. Bunge, Causality: The Place of the Causal Princple in Modern Science (Harvard University Press, Cambridge, Massachusetts, 1959). Reprinted as Causality and Modern Science, NY: Dover Books, 1979.
- Anonymous, Kuan Yin Tzu, T'ang Dynasty, Written in China during the T'ang dynasty. Partial translation in Joseph Needham, Science and Civilisation in China, vol. II (Cambridge University Press, 1956), p. 73.
- H. R. Lewis and C. H. Papadimitriou, Elements of the Theory of Computation, 2nd ed. (Prentice-Hall, Upper Saddle River, New Jersey, 1998).
- I. M. Gel'fand and A. M. Yaglom, Calculation of the amount of information about a random function contained in another such function, Uspekhi Matematicheski Nauk 12:3–52 (1956). Trans. in American Mathematical Society Translations 12(2):199û246 (1959).
- A. N. Kolmogorov, Interpolation und extrapolation von stationären zufälligen folgen, Bull. Acad. Sci. U.S.S.R., Math. 3:3–14 (1941). In Russian with German summary.
Cited by
Sorted by citations
An information integration theory of consciousness
Tononi, G. (2004) · BMC Neuroscience · doi:10.1186/1471-2202-5-42 · Cited by 1,958
“A related measure could be constructed using the formalism of ε-machines [63].”
MethodLadyman, J., Lambert, J., & Wiesner, K. (2013) · European Journal for Philosophy of Science · doi:10.1007/s13194-012-0056-8 · Cited by 846
Supply-chain networks: a complex adaptive systems perspective
Surana, A., Kumara, S. R. T., Greaves, M., & Raghavan, U. N. (2005) · International Journal of Production Research · doi:10.1080/00207540500142274 · Cited by 649
Predictability, Complexity, and Learning
Bialek, W., Nemenman, I. M., & Tishby, N. (2001) · Neural Computation · doi:10.1162/089976601753195969 · Cited by 524
How Efficiency Shapes Human Language
Gibson, E., Futrell, R., Piantadosi, S. P., Dautriche, I., Mahowald, K., Bergen, L., & Levy, R. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2019.02.003 · Cited by 485
Metadata
- Authors
- Shalizi, C. R., & Crutchfield, J. P.
- Affiliations
- Santa Fe Institute (US)
- Venue
- Journal of Statistical Physics
- Published
- 2001-08
- Volume
- 104
- Issue
- 3-4
- Pages
- 817-879
- ISSN
- 0022-4715 (ISSN-L)
- 1572-9613
- OpenAlex
- W1551871633
- Cited by
- 471
- References
- 152
- Citations by year
- 2026: 31 · 2025: 22 · 2024: 28 · 2023: 15 · 2022: 20 · 2021: 16 · 2020: 23 · 2019: 23 · 2018: 25 · 2017: 29 · 2016: 24 · 2015: 24 · 2014: 20 · 2013: 26 · 2012: 20
- FWCI
- 11.27
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- Journal of Statistical Physics (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Science Foundation (9970158)
- Santa Fe Institute
- Science Foundation Ireland
- Defense Advanced Research Projects Agency
- Office of Naval Research (N00014-95-1-0975)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computability, Logic, AI Algorithms
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Cellular Automata and Applications
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Systems and Dynamics
- Keywords
- computational mechanics, causal states, structural complexity, prediction, minimal representation, randomness measures, ergodic theory, information theory
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