Algorithmic Information Theory

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Algorithmic Information Theory

Author : Gregory. J. Chaitin
Publisher : Cambridge University Press
ISBN 13 : 9780521616041
Total Pages : 192 pages
Book Rating : 4.6/5 (16 download)

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Book Synopsis Algorithmic Information Theory by : Gregory. J. Chaitin

Download or read book Algorithmic Information Theory written by Gregory. J. Chaitin and published by Cambridge University Press. This book was released on 2004-12-02 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chaitin, the inventor of algorithmic information theory, presents in this book the strongest possible version of Gödel's incompleteness theorem, using an information theoretic approach based on the size of computer programs. One half of the book is concerned with studying the halting probability of a universal computer if its program is chosen by tossing a coin. The other half is concerned with encoding the halting probability as an algebraic equation in integers, a so-called exponential diophantine equation.

A Statistical Mechanical Interpretation of Algorithmic Information Theory

Author : Kohtaro Tadaki
Publisher : Springer Nature
ISBN 13 : 9811507392
Total Pages : 136 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis A Statistical Mechanical Interpretation of Algorithmic Information Theory by : Kohtaro Tadaki

Download or read book A Statistical Mechanical Interpretation of Algorithmic Information Theory written by Kohtaro Tadaki and published by Springer Nature. This book was released on 2019-11-11 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first one that provides a solid bridge between algorithmic information theory and statistical mechanics. Algorithmic information theory (AIT) is a theory of program size and recently is also known as algorithmic randomness. AIT provides a framework for characterizing the notion of randomness for an individual object and for studying it closely and comprehensively. In this book, a statistical mechanical interpretation of AIT is introduced while explaining the basic notions and results of AIT to the reader who has an acquaintance with an elementary theory of computation. A simplification of the setting of AIT is the noiseless source coding in information theory. First, in the book, a statistical mechanical interpretation of the noiseless source coding scheme is introduced. It can be seen that the notions in statistical mechanics such as entropy, temperature, and thermal equilibrium are translated into the context of noiseless source coding in a natural manner. Then, the framework of AIT is introduced. On this basis, the introduction of a statistical mechanical interpretation of AIT is begun. Namely, the notion of thermodynamic quantities, such as free energy, energy, and entropy, is introduced into AIT. In the interpretation, the temperature is shown to be equal to the partial randomness of the values of all these thermodynamic quantities, where the notion of partial randomness is a stronger representation of the compression rate measured by means of program-size complexity. Additionally, it is demonstrated that this situation holds for the temperature itself as a thermodynamic quantity. That is, for each of all the thermodynamic quantities above, the computability of its value at temperature T gives a sufficient condition for T to be a fixed point on partial randomness. In this groundbreaking book, the current status of the interpretation from both mathematical and physical points of view is reported. For example, a total statistical mechanical interpretation of AIT that actualizes a perfect correspondence to normal statistical mechanics can be developed by identifying a microcanonical ensemble in the framework of AIT. As a result, the statistical mechanical meaning of the thermodynamic quantities of AIT is clarified. In the book, the close relationship of the interpretation to Landauer's principle is pointed out.

Algorithmic Information Theory for Physicists and Natural Scientists

Author : Sean D Devine
Publisher :
ISBN 13 : 9780750326414
Total Pages : 238 pages
Book Rating : 4.3/5 (264 download)

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Book Synopsis Algorithmic Information Theory for Physicists and Natural Scientists by : Sean D Devine

Download or read book Algorithmic Information Theory for Physicists and Natural Scientists written by Sean D Devine and published by . This book was released on 2020-06-11 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic information theory (AIT), or Kolmogorov complexity as it is known to mathematicians, can provide a useful tool for scientists to look at natural systems, however, some critical conceptual issues need to be understood and the advances already made collated and put in a form accessible to scientists. This book has been written in the hope that readers will be able to absorb the key ideas behind AIT so that they are in a better position to access the mathematical developments and to apply the ideas to their own areas of interest. The theoretical underpinning of AIT is outlined in the earlier chapters, while later chapters focus on the applications, drawing attention to the thermodynamic commonality between ordered physical systems such as the alignment of magnetic spins, the maintenance of a laser distant from equilibrium, and ordered living systems such as bacterial systems, an ecology, and an economy. Key Features Presents a mathematically complex subject in language accessible to scientists Provides rich insights into modelling far-from-equilibrium systems Emphasises applications across range of fields, including physics, biology and econophysics Empowers scientists to apply these mathematical tools to their own research

Algorithmic Information Theory

Author : Peter Seibt
Publisher : Springer Science & Business Media
ISBN 13 : 3540332197
Total Pages : 446 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Algorithmic Information Theory by : Peter Seibt

Download or read book Algorithmic Information Theory written by Peter Seibt and published by Springer Science & Business Media. This book was released on 2007-02-15 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic Information Theory treats the mathematics of many important areas in digital information processing. It has been written as a read-and-learn book on concrete mathematics, for teachers, students and practitioners in electronic engineering, computer science and mathematics. The presentation is dense, and the examples and exercises are numerous. It is based on lectures on information technology (Data Compaction, Cryptography, Polynomial Coding) for engineers.

Information and Randomness

Author : Cristian Calude
Publisher : Springer Science & Business Media
ISBN 13 : 3662030497
Total Pages : 252 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Information and Randomness by : Cristian Calude

Download or read book Information and Randomness written by Cristian Calude and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Algorithmic information theory (AIT) is the result of putting Shannon's information theory and Turing's computability theory into a cocktail shaker and shaking vigorously", says G.J. Chaitin, one of the fathers of this theory of complexity and randomness, which is also known as Kolmogorov complexity. It is relevant for logic (new light is shed on Gödel's incompleteness results), physics (chaotic motion), biology (how likely is life to appear and evolve?), and metaphysics (how ordered is the universe?). This book, benefiting from the author's research and teaching experience in Algorithmic Information Theory (AIT), should help to make the detailed mathematical techniques of AIT accessible to a much wider audience.

Information Theory, Inference and Learning Algorithms

Author : David J. C. MacKay
Publisher : Cambridge University Press
ISBN 13 : 9780521642989
Total Pages : 694 pages
Book Rating : 4.6/5 (429 download)

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Book Synopsis Information Theory, Inference and Learning Algorithms by : David J. C. MacKay

Download or read book Information Theory, Inference and Learning Algorithms written by David J. C. MacKay and published by Cambridge University Press. This book was released on 2003-09-25 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.

Algorithmic Randomness and Complexity

Author : Rodney G. Downey
Publisher : Springer Science & Business Media
ISBN 13 : 0387684417
Total Pages : 883 pages
Book Rating : 4.3/5 (876 download)

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Book Synopsis Algorithmic Randomness and Complexity by : Rodney G. Downey

Download or read book Algorithmic Randomness and Complexity written by Rodney G. Downey and published by Springer Science & Business Media. This book was released on 2010-10-29 with total page 883 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computability and complexity theory are two central areas of research in theoretical computer science. This book provides a systematic, technical development of "algorithmic randomness" and complexity for scientists from diverse fields.

An Introduction to Kolmogorov Complexity and Its Applications

Author : Ming Li
Publisher : Springer Science & Business Media
ISBN 13 : 1475726066
Total Pages : 655 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis An Introduction to Kolmogorov Complexity and Its Applications by : Ming Li

Download or read book An Introduction to Kolmogorov Complexity and Its Applications written by Ming Li and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 655 pages. Available in PDF, EPUB and Kindle. Book excerpt: Briefly, we review the basic elements of computability theory and prob ability theory that are required. Finally, in order to place the subject in the appropriate historical and conceptual context we trace the main roots of Kolmogorov complexity. This way the stage is set for Chapters 2 and 3, where we introduce the notion of optimal effective descriptions of objects. The length of such a description (or the number of bits of information in it) is its Kolmogorov complexity. We treat all aspects of the elementary mathematical theory of Kolmogorov complexity. This body of knowledge may be called algo rithmic complexity theory. The theory of Martin-Lof tests for random ness of finite objects and infinite sequences is inextricably intertwined with the theory of Kolmogorov complexity and is completely treated. We also investigate the statistical properties of finite strings with high Kolmogorov complexity. Both of these topics are eminently useful in the applications part of the book. We also investigate the recursion theoretic properties of Kolmogorov complexity (relations with Godel's incompleteness result), and the Kolmogorov complexity version of infor mation theory, which we may call "algorithmic information theory" or "absolute information theory. " The treatment of algorithmic probability theory in Chapter 4 presup poses Sections 1. 6, 1. 11. 2, and Chapter 3 (at least Sections 3. 1 through 3. 4).

Universal Artificial Intelligence

Author : Marcus Hutter
Publisher : Springer Science & Business Media
ISBN 13 : 3540268774
Total Pages : 294 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Universal Artificial Intelligence by : Marcus Hutter

Download or read book Universal Artificial Intelligence written by Marcus Hutter and published by Springer Science & Business Media. This book was released on 2005-12-29 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Personal motivation. The dream of creating artificial devices that reach or outperform human inteUigence is an old one. It is also one of the dreams of my youth, which have never left me. What makes this challenge so interesting? A solution would have enormous implications on our society, and there are reasons to believe that the AI problem can be solved in my expected lifetime. So, it's worth sticking to it for a lifetime, even if it takes 30 years or so to reap the benefits. The AI problem. The science of artificial intelligence (AI) may be defined as the construction of intelligent systems and their analysis. A natural definition of a system is anything that has an input and an output stream. Intelligence is more complicated. It can have many faces like creativity, solving prob lems, pattern recognition, classification, learning, induction, deduction, build ing analogies, optimization, surviving in an environment, language processing, and knowledge. A formal definition incorporating every aspect of intelligence, however, seems difficult. Most, if not all known facets of intelligence can be formulated as goal driven or, more precisely, as maximizing some utility func tion. It is, therefore, sufficient to study goal-driven AI; e. g. the (biological) goal of animals and humans is to survive and spread. The goal of AI systems should be to be useful to humans.

Algorithmic Information Theory Physici

Author : DEVINE
Publisher : IOP Publishing Limited
ISBN 13 : 9780750326384
Total Pages : 238 pages
Book Rating : 4.3/5 (263 download)

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Book Synopsis Algorithmic Information Theory Physici by : DEVINE

Download or read book Algorithmic Information Theory Physici written by DEVINE and published by IOP Publishing Limited. This book was released on 2020-06-11 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic information theory (AIT), or Kolmogorov complexity as it is known to mathematicians, can provide a useful tool for scientists to look at natural systems, however, some critical conceptual issues need to be understood and the advances already made collated and put in a form accessible to scientists. This book has been written in the hope that readers will be able to absorb the key ideas behind AIT so that they are in a better position to access the mathematical developments and to apply the ideas to their own areas of interest. The theoretical underpinning of AIT is outlined in the earlier chapters, while later chapters focus on the applications, drawing attention to the thermodynamic commonality between ordered physical systems such as the alignment of magnetic spins, the maintenance of a laser distant from equilibrium, and ordered living systems such as bacterial systems, an ecology, and an economy. Key Features Presents a mathematically complex subject in language accessible to scientists Provides rich insights into modelling far-from-equilibrium systems Emphasises applications across range of fields, including physics, biology and econophysics Empowers scientists to apply these mathematical tools to their own research

Information Theory and Statistical Learning

Author : Frank Emmert-Streib
Publisher : Springer Science & Business Media
ISBN 13 : 0387848150
Total Pages : 443 pages
Book Rating : 4.3/5 (878 download)

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Book Synopsis Information Theory and Statistical Learning by : Frank Emmert-Streib

Download or read book Information Theory and Statistical Learning written by Frank Emmert-Streib and published by Springer Science & Business Media. This book was released on 2009 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: This interdisciplinary text offers theoretical and practical results of information theoretic methods used in statistical learning. It presents a comprehensive overview of the many different methods that have been developed in numerous contexts.

Kolmogorov Complexity and Algorithmic Randomness

Author : A. Shen
Publisher : American Mathematical Society
ISBN 13 : 1470470640
Total Pages : 511 pages
Book Rating : 4.4/5 (74 download)

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Book Synopsis Kolmogorov Complexity and Algorithmic Randomness by : A. Shen

Download or read book Kolmogorov Complexity and Algorithmic Randomness written by A. Shen and published by American Mathematical Society. This book was released on 2022-05-18 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: Looking at a sequence of zeros and ones, we often feel that it is not random, that is, it is not plausible as an outcome of fair coin tossing. Why? The answer is provided by algorithmic information theory: because the sequence is compressible, that is, it has small complexity or, equivalently, can be produced by a short program. This idea, going back to Solomonoff, Kolmogorov, Chaitin, Levin, and others, is now the starting point of algorithmic information theory. The first part of this book is a textbook-style exposition of the basic notions of complexity and randomness; the second part covers some recent work done by participants of the “Kolmogorov seminar” in Moscow (started by Kolmogorov himself in the 1980s) and their colleagues. This book contains numerous exercises (embedded in the text) that will help readers to grasp the material.

Classical and Quantum Information Theory

Author : Emmanuel Desurvire
Publisher : Cambridge University Press
ISBN 13 : 1139476653
Total Pages : 714 pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Classical and Quantum Information Theory by : Emmanuel Desurvire

Download or read book Classical and Quantum Information Theory written by Emmanuel Desurvire and published by Cambridge University Press. This book was released on 2009-02-19 with total page 714 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information theory lies at the heart of modern technology, underpinning all communications, networking, and data storage systems. This book sets out, for the first time, a complete overview of both classical and quantum information theory. Throughout, the reader is introduced to key results without becoming lost in mathematical details. Opening chapters present the basic concepts and various applications of Shannon's entropy, moving on to the core features of quantum information and quantum computing. Topics such as coding, compression, error-correction, cryptography and channel capacity are covered from classical and quantum viewpoints. Employing an informal yet scientifically accurate approach, Desurvire provides the reader with the knowledge to understand quantum gates and circuits. Highly illustrated, with numerous practical examples and end-of-chapter exercises, this text is ideal for graduate students and researchers in electrical engineering and computer science, and practitioners in the telecommunications industry. Further resources and instructor-only solutions are available at www.cambridge.org/9780521881715.

Elements of Information Theory

Author : Thomas M. Cover
Publisher : John Wiley & Sons
ISBN 13 : 1118585771
Total Pages : 788 pages
Book Rating : 4.1/5 (185 download)

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Book Synopsis Elements of Information Theory by : Thomas M. Cover

Download or read book Elements of Information Theory written by Thomas M. Cover and published by John Wiley & Sons. This book was released on 2012-11-28 with total page 788 pages. Available in PDF, EPUB and Kindle. Book excerpt: The latest edition of this classic is updated with new problem sets and material The Second Edition of this fundamental textbook maintains the book's tradition of clear, thought-provoking instruction. Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory. All the essential topics in information theory are covered in detail, including entropy, data compression, channel capacity, rate distortion, network information theory, and hypothesis testing. The authors provide readers with a solid understanding of the underlying theory and applications. Problem sets and a telegraphic summary at the end of each chapter further assist readers. The historical notes that follow each chapter recap the main points. The Second Edition features: * Chapters reorganized to improve teaching * 200 new problems * New material on source coding, portfolio theory, and feedback capacity * Updated references Now current and enhanced, the Second Edition of Elements of Information Theory remains the ideal textbook for upper-level undergraduate and graduate courses in electrical engineering, statistics, and telecommunications.

Algorithmic Number Theory: Efficient algorithms

Author : Eric Bach
Publisher : MIT Press
ISBN 13 : 9780262024051
Total Pages : 536 pages
Book Rating : 4.0/5 (24 download)

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Book Synopsis Algorithmic Number Theory: Efficient algorithms by : Eric Bach

Download or read book Algorithmic Number Theory: Efficient algorithms written by Eric Bach and published by MIT Press. This book was released on 1996 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume 1.

Algorithmic Learning in a Random World

Author : Vladimir Vovk
Publisher : Springer Science & Business Media
ISBN 13 : 9780387001524
Total Pages : 344 pages
Book Rating : 4.0/5 (15 download)

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Book Synopsis Algorithmic Learning in a Random World by : Vladimir Vovk

Download or read book Algorithmic Learning in a Random World written by Vladimir Vovk and published by Springer Science & Business Media. This book was released on 2005-03-22 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic Learning in a Random World describes recent theoretical and experimental developments in building computable approximations to Kolmogorov's algorithmic notion of randomness. Based on these approximations, a new set of machine learning algorithms have been developed that can be used to make predictions and to estimate their confidence and credibility in high-dimensional spaces under the usual assumption that the data are independent and identically distributed (assumption of randomness). Another aim of this unique monograph is to outline some limits of predictions: The approach based on algorithmic theory of randomness allows for the proof of impossibility of prediction in certain situations. The book describes how several important machine learning problems, such as density estimation in high-dimensional spaces, cannot be solved if the only assumption is randomness.

Information, Randomness & Incompleteness

Author : Gregory J. Chaitin
Publisher : World Scientific
ISBN 13 : 9789810201715
Total Pages : 332 pages
Book Rating : 4.2/5 (17 download)

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Book Synopsis Information, Randomness & Incompleteness by : Gregory J. Chaitin

Download or read book Information, Randomness & Incompleteness written by Gregory J. Chaitin and published by World Scientific. This book was released on 1990-01-01 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains in easily accessible form all the main ideas of the creator and principal architect of algorithmic information theory. This expanded second edition has added thirteen abstracts, a 1988 Scientific American Article, a transcript of a EUROPALIA 89 lecture, an essay on biology, and an extensive bibliography. Its new larger format makes it easier to read. Chaitin's ideas are a fundamental extension of those of Gdel and Turning and have exploded some basic assumptions of mathematics and thrown new light on the scientific method, epistemology, probability theory, and of course computer science and information theory.