In what sense is the Kolmogorov-Sinai entropy a measure for chaotic behaviour?—Bridging the gap between dynamical systems theory and communication theory

On an influential account, chaos is explained in terms of random behaviour; and random behaviour in turn is explained in terms of having positive Kolmogorov-Sinai entropy (KSE). Though intuitively plausible, the association of the KSE with random behaviour needs justification since the definition of the KSE does not make reference to any notion that is connected to randomness. I provide this justification for the case of Hamiltonian systems by proving that the KSE is equivalent to a generalized version of Shannon's communication-theoretic entropy under certain plausible assumptions. I then discuss consequences of this equivalence for randomness in chaotic dynamical systems. Introduction Elements of dynamical systems theory Entropy in communication theory Entropy in dynamical systems theory Comparison with other accounts Product versus process randomness.
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DOI 10.1093/bjps/55.3.411
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Joseph Berkovitz, Roman Frigg & Fred Kronz (2006). The Ergodic Hierarchy, Randomness and Hamiltonian Chaos. Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 37 (4):661-691.

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