The ergodic hierarchy, randomness and Hamiltonian chaos
Studies in History and Philosophy of Science Part B 37 (4):661-691 (2006)
| Abstract | Various processes are often classified as both deterministic and random or chaotic. The main difficulty in analysing the randomness of such processes is the apparent tension between the notions of randomness and determinism: what type of randomness could exist in a deterministic process? Ergodic theory seems to offer a particularly promising theoretical tool for tackling this problem by positing a hierarchy, the so-called ‘ergodic hierarchy’ (EH), which is commonly assumed to provide a hierarchy of increasing degrees of randomness. However, that notion of randomness requires clarification. The mathematical definition of EH does not make explicit appeal to randomness; nor does the usual way of presenting EH involve a specification of the notion of randomness that is supposed to underlie the hierarchy. In this paper we argue that EH is best understood as a hierarchy of random behaviour if randomness is explicated in terms of unpredictability. We then show that, contrary to common wisdom, EH is useful in characterising the behaviour of Hamiltonian dynamical systems. r 2006 Elsevier Ltd. All rights reserved. | |||||||||
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André Nies, Frank Stephan & Sebastiaan A. Terwijn (2005). Randomness, Relativization and Turing Degrees. Journal of Symbolic Logic 70 (2):515 - 535.
Antony Eagle, Chance Versus Randomness. Stanford Encyclopedia of Philosophy.
Roman Frigg (2004). In What Sense is the Kolmogorov-Sinai Entropy a Measure for Chaotic Behaviour?—Bridging the Gap Between Dynamical Systems Theory and Communication Theory. British Journal for the Philosophy of Science 55 (3):411 - 434.
Roman Frigg & Joseph Berkovitz (2011). The Ergodic Hierarchy. Stanford Encyclopedia of Philosophy.
Joseph Berkovitz, Roman Frigg & Fred Kronz (2006). The Ergodic Hierarchy, Randomness and Hamiltonian Chaos☆. Studies in History and Philosophy of Science Part B 37 (4):661-691.
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