Intended for use in an introductory graduate course in theoretical computer science, this text contains material that should be core knowledge in the theory of computation for all graduates in computer science. It is self-contained and is best suited for a one semester course. The text starts with classical computability theory which forms the basis for complexity theory. This has the pedagogical advantage that students learn a qualitative subject before advancing to a quantitative one. Since this is a graduate course, students should have some knowledge of such topics as automata theory, formal languages, computability theory, or complexity theory.
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From the reviews:
"The difference between this new introductory graduate textbook in theoretical computer science and other texts is that the authors have chosen to concentrate on computability theory and computational complexity theory. They motivate this focus by pointing out that most students have been introduced to the theory of automata and formal languages as undergraduates. The topics are treated in depth and in full formal detail. Explicit homework assignments are tightly integrated into the exposition of the material." --Computing Reviews
"This book is intended for use in a modern graduate course in the theory of computing. ... Mainly all old classical complexity results as well as a relatively recent result that space-bounded classes are closed under complements are included into the book. The textbook is self-contained. A list of useful homework problems is appended to each chapter. The book is well written and is recommended to students as well as specialists in theoretical computer science." (Anatoly V. Anisimov, Zentralblatt MATH, Vol. 1033 (8), 2004)
"This book is a solid textbook suited for one- or two-semester graduate courses on the theory of computing. ...The authors are two leading researchers in the field of theoretical computer sciences, most notably complexity theory. ... This textbook is an excellent resource and guide for those looking to develop a solid grounding in the theory of computing. Beginning graduates, advanced undergraduates and professionals involved in theoretical computer science, complexity theory and computability will find this book an essential and practical learning tool." (André Grosse, The Computer Journal, Vol. 45 (4), 2002)
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Seller: Ammareal, Morangis, France
Hardcover. Condition: Très bon. Ancien livre de bibliothèque. Edition 2001. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 2001. Ammareal gives back up to 15% of this item's net price to charity organizations. Seller Inventory # E-577-788
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Seller: Bookbot, Prague, Czech Republic
Hardcover. Condition: As New. Leichte Kratzer / Abnutzungen / Druckstellen. This volume presents essential materials in the theory of computation, structured to be self-contained. It begins with a chapter on key mathematical concepts and notations, then progresses from qualitative aspects of classical computability to the quantitative dimensions of complexity theory. Dedicated chapters explore undecidability, NP-completeness, and relative computability, emphasizing the limitations of computability and the distinction between feasible and intractable problems. Key topics include fundamental concepts in modern complexity theory, such as NP-completeness, NP-hardness, the polynomial hierarchy, and complete problems across complexity classes. The book consolidates information typically found only in research literature, simplifying complex topics like complements of complexity classes, search problems, and intermediate problems in NP. It also provides essential mathematical background, covering logic, number theory, and algebra. Numerous exercises and supplementary problems are included to reinforce learning and support self-study. With its accessible format and logical organization, this text serves as an excellent resource for those seeking a solid foundation in computing theory. It is particularly valuable for beginning graduates, advanced undergraduates, and professionals in theoretical computer science, complexity theory, and computability. Seller Inventory # ed16d363-4975-44d0-b3a5-aae0a886e4ae
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