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Why a book on fault-tolerant search algorithms? Searching is one of the fundamental problems in computer science. Time and again algorithmic and combinatorial issues originally studied in the context of search find application in the most diverse areas of computer science and discrete mathematics. On the other hand, fault-tolerance is a necessary ingredient of computing. Due to their inherent complexity, information systems are naturally prone to errors, which may appear at any level – as imprecisions in the data, bugs in the software, or transient or permanent hardware failures. This book provides a concise, rigorous and up-to-date account of different approaches to fault-tolerance in the context of algorithmic search theory. Thanks to their basic structure, search problems offer insights into how fault-tolerant techniques may be applied in various scenarios. In the first part of the book, a paradigmatic model for fault-tolerant search is presented, the Ulam—Rényi problem. Following a didactic approach, the author takes the reader on a tour of Ulam—Rényi problem variants of increasing complexity. In the context of this basic model, fundamental combinatorial and algorithmic issues in the design of fault-tolerant search procedures are discussed. The algorithmic efficiency achievable is analyzed with respect to the statistical nature of the error sources, and the amount of information on which the search algorithm bases its decisions. In the second part of the book, more general models of faults and fault-tolerance are considered. Special attention is given to the application of fault-tolerant search procedures to specific problems in distributed computing, bioinformatics and computational learning. This book will be of special value to researchers from the areas of combinatorial search and fault-tolerant computation, but also to researchers in learning and coding theory, databases, and artificial intelligence. Only basic training in discrete mathematics is assumed.
The book investigates how to design and analyze search algorithms that can function reliably even when faced with errors in data, software, or hardware. It presents a rigorous and up-to-date account of different approaches to fault-tolerance within algorithmic search theory, highlighting how the structure of search problems offers insights into applying these techniques. The work is divided into two parts: the first introduces a paradigmatic model, the Ulam—Rényi problem, and explores its variants to discuss fundamental combinatorial and algorithmic issues, analyzing efficiency based on error statistics and information availability. The second part extends the discussion to more general fault models and their applications in distributed computing, bioinformatics, and computational learning.
This book is intended for researchers in combinatorial search and fault-tolerant computation, as well as those in learning theory, coding theory, databases, and artificial intelligence. The content assumes only basic training in discrete mathematics, suggesting an accessible yet rigorous approach to complex topics. The structured presentation, moving from a basic model to more general applications, indicates a pedagogical design aimed at building understanding systematically. Its focus on practical applications in diverse fields like distributed computing and bioinformatics suggests its relevance to contemporary research challenges.
Page Count:
207
Publication Date:
2012-01-01
ISBN-10:
3642173268
ISBN-13:
9783642173264
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