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2010•arXiv (Cornell University)Open access

Kolmogorov Complexity in perspective. Part I: Information Theory and Randomnes

Marie Ferbus-Zanda, Serge Grigorieff

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Abstract

We survey diverse approaches to the notion of information: from Shannon entropy to Kolmogorov complexity. Two of the main applications of Kolmogorov complexity are presented: randomness and classification. The survey is divided in two parts in the same volume. Part I is dedicated to information theory and the mathematical formalization of randomness based on Kolmogorov complexity. This last application goes back to the 60's and 70's with the work of Martin-Löf, Schnorr, Chaitin, Levin, and has gained new impetus in the last years.

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We survey diverse approaches to the notion of information: from Shannon entropy to Kolmogorov complexity. Two of the main applications of Kolmogorov complexity are presented: randomness and classification. The survey is divided in two parts in the same volume. Part I is dedicated to information theory and the mathematical formalization of randomness based on Kolmogorov complexity. This last application goes back to the 60's and 70's with the work of Martin-Löf, Schnorr, Chaitin, Levin, and has gained new impetus in the last years.

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Available abstract

We survey diverse approaches to the notion of information: from Shannon entropy to Kolmogorov complexity. Two of the main applications of Kolmogorov complexity are presented: randomness and classification. The survey is divided in two parts in the same volume. Part I is dedicated to information theory and the mathematical formalization of randomness based on Kolmogorov complexity. This last application goes back to the 60's and 70's with the work of Martin-Löf, Schnorr, Chaitin, Levin, and has gained new impetus in the last years.

Key concepts: Perspective (graphical), Kolmogorov complexity, Information theory, Kolmogorov structure function, Cognitive science, Epistemology, Sociology, Psychology

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