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Texts in Computer Science: Computability and Complexity Theory

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  • 194 pages
  • 7 hours of reading

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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.

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Texts in Computer Science: Computability and Complexity Theory, Steven Homer, Alan L. Selman

Language
Released
2001
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(Hardcover),
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Very Good
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€7.49

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Title
Texts in Computer Science: Computability and Complexity Theory
Language
English
Publisher
Springer
Released
2001
Format
Hardcover
Pages
194
ISBN10
0387950559
ISBN13
9780387950556
Series
Description
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.