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Related papers: Kolmogorov Complexity and Information Content

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Kolmogorov complexity theory is used to tell what the algorithmic informational content of a string is. It is defined as the length of the shortest program that describes the string. We present a programming language that can be used to…

Category Theory · Mathematics 2013-06-13 Noson S. Yanofsky

The notion of Kolmogorov complexity (=the minimal length of a program that generates some object) is often useful as a kind of language that allows us to reformulate some notions and therefore provide new intuition. In this survey we…

Information Theory · Computer Science 2011-03-01 Alexander Shen

The word "complexity" is most often used as a meta--linguistic expression referring to certain intuitive characteristics of a natural system and/or its scientific description. These characteristics may include: sheer amount of data that…

History and Overview · Mathematics 2013-01-03 Yuri I. Manin

I discuss several aspects of information theory and its relationship to physics and neuroscience. The unifying thread of this somewhat chaotic essay is the concept of Kolmogorov or algorithmic complexity (Kolmogorov Complexity, for short).…

General Physics · Physics 2007-05-23 Giulio Ruffini

In analogy of classical Kolmogorov complexity we develop a theory of the algorithmic information in bits contained in any one of continuously many pure quantum states: quantum Kolmogorov complexity. Classical Kolmogorov complexity coincides…

Quantum Physics · Physics 2007-05-23 Paul Vitanyi

Kolmogorov complexity measures the algorithmic complexity of a finite binary string $\sigma$ in terms of the length of the shortest description $\sigma^*$ of $\sigma$. Traditionally, the length of a string is taken to measure the amount of…

Computational Complexity · Computer Science 2019-06-14 Cameron Fraize , Christopher P. Porter

Kolmogorov complexity is a measure of the information contained in a binary string. We investigate here the notion of quantum Kolmogorov complexity, a measure of the information required to describe a quantum state. We show that for any…

Quantum Physics · Physics 2007-05-23 C. Mora , H. Briegel , B. Kraus

It is not obvious what fraction of all the potential information residing in the molecules and structures of living systems is significant or meaningful to the system. Sets of random sequences or identically repeated sequences, for example,…

Information Theory · Computer Science 2008-01-28 David J. Galas , Matti Nykter , Gregory W. Carter , Nathan D. Price , Ilya Shmulevich

In this paper we give a definition for quantum Kolmogorov complexity. In the classical setting, the Kolmogorov complexity of a string is the length of the shortest program that can produce this string as its output. It is a measure of the…

Quantum Physics · Physics 2007-05-23 Andre Berthiaume , Wim van Dam , Sophie Laplante

We introduce algorithmic information theory, also known as the theory of Kolmogorov complexity. We explain the main concepts of this quantitative approach to defining `information'. We discuss the extent to which Kolmogorov's and Shannon's…

Information Theory · Computer Science 2008-09-17 Peter D. Grunwald , Paul M. B. Vitanyi

We survey the diverse approaches to the notion of information content: from Shannon entropy to Kolmogorov complexity. The main applications of Kolmogorov complexity are presented namely, the mathematical notion of randomness (which goes…

Logic · Mathematics 2008-01-03 Marie Ferbus-Zanda , Serge Grigorieff

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…

Logic in Computer Science · Computer Science 2010-10-20 Marie Ferbus-Zanda , Serge Grigorieff

"Information Processing" is a recently launched buzzword whose meaning is vague and obscure even for the majority of its users. The reason for this is the lack of a suitable definition for the term "information". In my attempt to amend this…

Artificial Intelligence · Computer Science 2013-03-12 Emanuel Diamant

Algorithmic information theory studies description complexity and randomness and is now a well known field of theoretical computer science and mathematical logic. There are several textbooks and monographs devoted to this theory where one…

Information Theory · Computer Science 2015-04-21 Alexander Shen

The Kolmogorov complexity of a string is the length of its shortest description. We define a second quantised Kolmogorov complexity where the length of a description is defined to be the average length of its superposition. We discuss this…

Quantum Physics · Physics 2008-09-17 Caroline Rogers , Vlatko Vedral , Rajagopal Nagarajan

This is a short introduction to Kolmogorov Complexity. The interested reader is referred to the text books by Cover & Thomas as well as Li & V\'itanyi, which cover the fields of information theory and Kolmogorov complexity in depth and with…

Computational Complexity · Computer Science 2010-05-17 Volker Nannen

The information in an individual finite object (like a binary string) is commonly measured by its Kolmogorov complexity. One can divide that information into two parts: the information accounting for the useful regularity present in the…

Computational Complexity · Computer Science 2007-05-23 Paul Vitanyi

We compare the elementary theories of Shannon information and Kolmogorov complexity, the extent to which they have a common purpose, and where they are fundamentally different. We discuss and relate the basic notions of both theories:…

Information Theory · Computer Science 2020-07-21 Peter Grunwald , Paul Vitanyi

Kolmogorov complexity is the length of the ultimately compressed version of a file (that is, anything which can be put in a computer). Formally, it is the length of a shortest program from which the file can be reconstructed. We discuss the…

Information Theory · Computer Science 2020-04-22 Paul Vitanyi

Kolmogorov argued that the concept of information exists also in problems with no underlying stochastic model (as Shannon's information representation) for instance, the information contained in an algorithm or in the genome. He introduced…

Discrete Mathematics · Computer Science 2008-07-01 Joel Ratsaby
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