Kolmogorov complexity and information theory. With an interpretation in terms of questions and answers

Journal of Logic, Language and Information 12 (4):497-529 (2003)
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Abstract

We compare the elementary theories of Shannon information and Kolmogorov complexity, the extent to which they have a common purpose, and wherethey are fundamentally different. We discuss and relate the basicnotions of both theories: Shannon entropy, Kolmogorov complexity, Shannon mutual informationand Kolmogorov (``algorithmic'') mutual information. We explainhow universal coding may be viewed as a middle ground betweenthe two theories. We consider Shannon's rate distortion theory, whichquantifies useful (in a certain sense) information.We use the communication of information as our guiding motif, and we explain howit relates to sequential question-answer sessions.

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Citations of this work

Bohmian Mechanics is Not Deterministic.Klaas Landsman - 2022 - Foundations of Physics 52 (4):1-17.
A Scientific Metaphysical Naturalisation of Information.Bruce Long - 2018 - Dissertation, University of Sydney
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Strengthening Weak Emergence.Nora Berenstain - 2020 - Erkenntnis 87 (5):2457-2474.
Effective Complexity: In Which Sense is It Informative?Esteban Céspedes & Miguel Fuentes - 2020 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 51 (3):359-374.

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References found in this work

A Mathematical Theory of Communication.Claude Elwood Shannon - 1948 - Bell System Technical Journal 27 (April 1924):379–423.
Quality and Quantity of Information Exchange.Robert van Rooy - 2003 - Journal of Logic, Language and Information 12 (4):423-451.
Quality and quantity of information exchange.Robert van Rooy - 2003 - Journal of Logic, Language and Information 12 (4):423-451.
On the Mathematical Foundations of Theoretical Statistics.Ronald A. Fisher - 1922 - Philosophical Transactions of the Royal Society of London. Series A 222:309--368.

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