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IS RANDOMNESS “NATIVE” TO COMPUTER SCIENCE?

Marie Ferbus-Zanda, Serge Grigorieff

Open publisher page 5 citations

Abstract

We survey the Kolmogorov's approach to the notion of randomness through the Kolmogorov complexity theory. The original motivation of Kolmogorov was to give up a quantitative definition of information. In this theory, an object is randomness in the sense that it has a large information content. Afterwards, we present parts of the work of Martin-Lof, Schnorr, Chaitin and Levin which supply a mathematical notion of randomness throughout diverse theories from the the 60' up to recently.

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What this paper is about

We survey the Kolmogorov's approach to the notion of randomness through the Kolmogorov complexity theory. The original motivation of Kolmogorov was to give up a quantitative definition of information. In this theory, an object is randomness in the sense that it has a large information content. Afterwards, we present parts of the work of Martin-Lof, Schnorr, Chaitin and Levin which supply a mathematical notion of randomness throughout diverse theories from the the 60' up to recently.

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OpenAlex reports 5 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

We survey the Kolmogorov's approach to the notion of randomness through the Kolmogorov complexity theory. The original motivation of Kolmogorov was to give up a quantitative definition of information. In this theory, an object is randomness in the sense that it has a large information content. Afterwards, we present parts of the work of Martin-Lof, Schnorr, Chaitin and Levin which supply a mathematical notion of randomness throughout diverse theories from the the 60' up to recently.

Key concepts: Randomness, Kolmogorov complexity, Kolmogorov structure function, Computer science, Theoretical computer science, Object (grammar), Content (measure theory), Epistemology

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