Amazon cover image
Image from Amazon.com

An Introduction to Kolmogorov Complexity and Its Applications [electronic resource] /

By: Contributor(s): Material type: TextTextSeries: Texts in Computer SciencePublisher: Cham : Springer International Publishing : Imprint: Springer, 2019Edition: 4th ed. 2019Description: XXIII, 834 p. 1 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783030112981
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 519 23
LOC classification:
  • T57-57.97
Online resources:
Contents:
Preliminaries -- Algorithmic Complexity -- Algorithmic Prefix Complexity -- Algorithmic Probability -- Inductive Reasoning -- The Incompressibility Method -- Resource-Bounded Complexity -- Physics, Information, and Computation.
In: Springer Nature eBookSummary: This must-read textbook presents an essential introduction to Kolmogorov complexity (KC), a central theory and powerful tool in information science that deals with the quantity of information in individual objects. The text covers both the fundamental concepts and the most important practical applications, supported by a wealth of didactic features. This thoroughly revised and enhanced fourth edition includes new and updated material on, amongst other topics, the Miller-Yu theorem, the Gács-Kučera theorem, the Day-Gács theorem, increasing randomness, short lists computable from an input string containing the incomputable Kolmogorov complexity of the input, the Lovász local lemma, sorting, the algorithmic full Slepian-Wolf theorem for individual strings, multiset normalized information distance and normalized web distance, and conditional universal distribution. Topics and features: Describes the mathematical theory of KC, including the theoriesof algorithmic complexity and algorithmic probability Presents a general theory of inductive reasoning and its applications, and reviews the utility of the incompressibility method Covers the practical application of KC in great detail, including the normalized information distance (the similarity metric) and information diameter of multisets in phylogeny, language trees, music, heterogeneous files, and clustering Discusses the many applications of resource-bounded KC, and examines different physical theories from a KC point of view Includes numerous examples that elaborate the theory, and a range of exercises of varying difficulty (with solutions) Offers explanatory asides on technical issues, and extensive historical sections Suggests structures for several one-semester courses in the preface As the definitive textbook on Kolmogorov complexity, this comprehensive and self-contained work is an invaluable resource for advanced undergraduate students, graduate students, and researchers in all fields of science. “Li and Vitányi have provided an ideal book for the exploration of a deep, beautiful and important part of computer science.” -- Juris Hartmanis, Turing Award Winner 1993, Cornell University, Ithaca, NY. “The book is likely to remain the standard treatment of Kolmogorov complexity for a long time.” -- Jorma J. Rissanen, IBM Research, California. “The book of Li and Vitányi is unexcelled.” -- Ray J. Solomonoff, Oxbridge Research, Cambridge, Massachusetts.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
No physical items for this record

Preliminaries -- Algorithmic Complexity -- Algorithmic Prefix Complexity -- Algorithmic Probability -- Inductive Reasoning -- The Incompressibility Method -- Resource-Bounded Complexity -- Physics, Information, and Computation.

This must-read textbook presents an essential introduction to Kolmogorov complexity (KC), a central theory and powerful tool in information science that deals with the quantity of information in individual objects. The text covers both the fundamental concepts and the most important practical applications, supported by a wealth of didactic features. This thoroughly revised and enhanced fourth edition includes new and updated material on, amongst other topics, the Miller-Yu theorem, the Gács-Kučera theorem, the Day-Gács theorem, increasing randomness, short lists computable from an input string containing the incomputable Kolmogorov complexity of the input, the Lovász local lemma, sorting, the algorithmic full Slepian-Wolf theorem for individual strings, multiset normalized information distance and normalized web distance, and conditional universal distribution. Topics and features: Describes the mathematical theory of KC, including the theoriesof algorithmic complexity and algorithmic probability Presents a general theory of inductive reasoning and its applications, and reviews the utility of the incompressibility method Covers the practical application of KC in great detail, including the normalized information distance (the similarity metric) and information diameter of multisets in phylogeny, language trees, music, heterogeneous files, and clustering Discusses the many applications of resource-bounded KC, and examines different physical theories from a KC point of view Includes numerous examples that elaborate the theory, and a range of exercises of varying difficulty (with solutions) Offers explanatory asides on technical issues, and extensive historical sections Suggests structures for several one-semester courses in the preface As the definitive textbook on Kolmogorov complexity, this comprehensive and self-contained work is an invaluable resource for advanced undergraduate students, graduate students, and researchers in all fields of science. “Li and Vitányi have provided an ideal book for the exploration of a deep, beautiful and important part of computer science.” -- Juris Hartmanis, Turing Award Winner 1993, Cornell University, Ithaca, NY. “The book is likely to remain the standard treatment of Kolmogorov complexity for a long time.” -- Jorma J. Rissanen, IBM Research, California. “The book of Li and Vitányi is unexcelled.” -- Ray J. Solomonoff, Oxbridge Research, Cambridge, Massachusetts.

There are no comments on this title.

to post a comment.
© 2024 IIIT-Delhi, library@iiitd.ac.in