An Introduction to Kolmogorov Complexity and Its Applications


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Description

Written by two experts in the field, this is the only comprehensive and unified treatment of the central ideas and applications of Kolmogorov complexity. The book presents a thorough treatment of the subject with a wide range of illustrative applications. Such applications include the randomness of finite objects or infinite sequences, Martin-Loef tests for randomness, information theory, computational learning theory, the complexity of algorithms, and the thermodynamics of computing. It will be ideal for advanced undergraduate students, graduate students, and researchers in computer science, mathematics, cognitive sciences, philosophy, artificial intelligence, statistics, and physics. The book is self-contained in that it contains the basic requirements from mathematics and computer science. Included are also numerous problem sets, comments, source references, and hints to solutions of problems. New topics in this edition include Omega numbers, Kolmogorov-Loveland randomness, universal learning, communication complexity, Kolmogorov's random graphs, time-limited universal distribution, Shannon information and others.



Author: Ming Li, Paul Vitányi
Publisher: Springer
Published: 06/26/2019
Pages: 834
Binding Type: Hardcover
Weight: 4.20lbs
Size: 10.16h x 7.20w x 1.60d
ISBN13: 9783030112974
ISBN10: 3030112977
BISAC Categories:
- Mathematics | Applied
- Computers | Information Theory
- Computers | Computer Science

About the Author
Dr. Paul M.B. Vitányi is a CWI Fellow at the Netherlands National Research Institute for Mathematics and Computer Science (CWI), and a Professor of Computer Science at the University of Amsterdam. Dr. Ming Li is Canada Research Chair in Bioinformatics and University Professor at the University of Waterloo, ON, Canada.
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Textbook & Academic Authors Association 2020 McGuffey Longevity Award Winner!
The judges said:
"An Introduction to Kolmogorov complexity and Its Applications has been an outstanding textbook and comprehensive reference for on information complexity for over twenty years. This new edition continues that tradition by laying a terrific foundation in the early chapters for the more advanced theories and concepts that follow. Each new theorem and corollary flows naturally and logically from what came before."