Limits of Computation: An Introduction to the Undecidable and the Intractable
Autor Edna E. Reiter, Clayton Matthew Johnsonen Limba Engleză Hardback – 29 oct 2012
The book enables readers to understand:
- What does it mean for a problem to be unsolvable or to be NP-complete?
- What is meant by a computation and what is a general model of a computer?
- What does it mean for an algorithm to exist and what kinds of problems have no algorithm?
- What problems have algorithms but the algorithm may take centuries to finish?
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Specificații
ISBN-13: 9781439882061
ISBN-10: 1439882061
Pagini: 279
Ilustrații: 79 b/w images and 3 tables
Dimensiuni: 156 x 234 x 23 mm
Greutate: 1.3 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
ISBN-10: 1439882061
Pagini: 279
Ilustrații: 79 b/w images and 3 tables
Dimensiuni: 156 x 234 x 23 mm
Greutate: 1.3 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
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Public țintă
Professional Practice & DevelopmentCuprins
Introduction. Set Theory. Languages: Alphabets, Strings, and Languages. Algorithms. Turing Machines. Turing-Completeness. Undecidability. Undecidability and Reducibility. Classes NP and NP-Complete. More NP-Complete Problems. Other Interesting Questions and Classes. Bibliography. Index.
Notă biografică
Edna E. Reiter, Ph.D., is the current Chair of the Department of Mathematics and Computer Science at California State University, East Bay (CSUEB). Her research interests include noncommutative ring theory and theoretical aspects of computer science.
Clayton Matthew Johnson, Ph.D., is the graduate coordinator for all M.S. students and the incoming Chair of the Department of Mathematics and Computer Science at CSUEB. His research interests include genetic algorithms and machine learning.
Drs. Reiter and Johnson developed the subject matter for the CSUEB Computation and Complexity course, which is required for all students in the computer science M.S. program. The course covers the hard problems of computer science—those that are intractable or undecidable. The material in this book has been tested on multiple sections of CSUEB students.
Clayton Matthew Johnson, Ph.D., is the graduate coordinator for all M.S. students and the incoming Chair of the Department of Mathematics and Computer Science at CSUEB. His research interests include genetic algorithms and machine learning.
Drs. Reiter and Johnson developed the subject matter for the CSUEB Computation and Complexity course, which is required for all students in the computer science M.S. program. The course covers the hard problems of computer science—those that are intractable or undecidable. The material in this book has been tested on multiple sections of CSUEB students.
Recenzii
"… a very basic, reader friendly introduction to computational complexity theory. What sets their book apart from others on the topic is its leisurely pace. … Because the book is so readable, it is likely that its primary audience will include students who experienced difficulties with other books on the topic. However, those students would probably benefit from more exercises than this volume provides, especially full solutions, at least for some exercises. … Highly recommended. Lower-division undergraduates.
—M Bona, University of Florida in CHOICE Magazine, June 2013
"This excellent book on DSNs has a wealth of information for researchers, engineers, and scientists. It could be used as a textbook for graduate-level and doctoral courses on DSNs, and would also serve as a reference for engineers, scientists, and researchers working in this field."
—Computing Reviews, April 2013
—M Bona, University of Florida in CHOICE Magazine, June 2013
"This excellent book on DSNs has a wealth of information for researchers, engineers, and scientists. It could be used as a textbook for graduate-level and doctoral courses on DSNs, and would also serve as a reference for engineers, scientists, and researchers working in this field."
—Computing Reviews, April 2013
Descriere
Developed from the authors’ course on computational complexity theory, this book offers a gentle introduction to the theory of computational complexity. It explains the difficulties of computation, addressing problems that have no algorithm at all and problems that cannot be solved efficiently. The text assumes no prior knowledge of automata, advanced algorithmic analysis, and formal languages. Each chapter presents the fundamentals, examples, complete proofs of theorems, and a wide range of exercises. PowerPoint slides are available for download at www.crcpress.com.