Cristian S. Calude

Information and Randomness (eBook, PDF)

An Algorithmic Perspective

• Format: PDF

Produktbeschreibung

The book presents in a mathematical clear way the fundamentals of algorithmic information theory and a few selected applications. This 2nd edition presents new and important results obtained in recent years: the characterization of computable enumerable random reals, the construction of an Omega Number for which ZFC cannot determine any digits, and the first successful attempt to compute the exact values of 64 bits of a specific Omega Number. Finally, the book contains a discussion of some interesting philosophical questions related to randomness and mathematical knowledge.

"Professor Calude has produced a first-rate exposition of up-to-date work in information and randomness." D.S. Bridges, Canterbury University, co-author, with Errett Bishop, of Constructive Analysis;

"The second edition of this classic work is highly recommended to anyone interested in algorithmic information and randomness." G.J. Chaitin, IBM Research Division, New York, author of Conversations with a Mathematician;

"This book is a must for a comprehensive introduction to algorithmic information theory and for anyone interested in its applications in the natural sciences." K. Svozil, Technical University of Vienna, author of Randomness & Undecidability in Physics

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 468
• Erscheinungstermin: 9. März 2013
• Englisch
• ISBN-13: 9783662049785
• Artikelnr.: 53134939

Autorenporträt

Cristian S. Calude, Auckland University, Auckland, New Zealand

Inhaltsangabe

1 Mathematical Background.- 2 Noiseless Coding.- 3 Program-size.- 4 Computably Enumerable Instantaneous Codes.- 5 Random Strings.- 6 Random Sequences.- 7 Computably Enumerable Random Reals.- 8 Randomness and Incompleteness.- 9 Applications.- 10 Open Problems.- Notation Index.- Name Index.

Rezensionen

From the reviews of the second edition: "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." (PHINEWS, Vol. 2, October 2002)