Du Ding-Zhu, Ko Ker-I. Theory of Computational Complexity

Wiley. Hoboken, NJ, USA, Second Edition. 2014. 512 p. Includes references and index. ISBN: 978-1-118-30608-6 (cloth)A thorough revision based on advances in the field of computational complexity and readers’ feedback, the Second Edition of Theory of Computational Complexity presents updates to the principles and applications essential to understanding modern computational complexity theory. The new edition continues to serve as a comprehensive resource on the use of software and computational approaches for solving algorithmic problems and the related difficulties that can be encountered.Maintaining extensive and detailed coverage, Theory of Computational Complexity, Second Edition examines the theory and methods behind complexity theory, such as computational models, decision tree complexity, circuit complexity, and probabilistic complexity. The Second Edition also features recent developments on areas such as NP-completeness theory, as well as:A new combinatorial proof of the PCP theorem based on the notion of expander graphs, a research area in the field of computer science
Additional exercises at varying levels of difficulty to further test comprehension of the presented materialEnd-of-chapter literature reviews that summarize each topic and offer additional sources for further studyTheory of Computational Complexity, Second Edition is an excellent textbook for courses on computational theory and complexity at the graduate-level. The book is also a useful reference for practitioners in the fields of computer science, engineering, and mathematics who utilize state-of-the-art software and computational methods to conduct research.Uniform Complexity
Models of Computation and Complexity Classes
NP-Completeness
The Polynomial-Time Hierarchy and Polynomial Space
Structure of NP
Nonuniform Complexity
Decision Trees
Circuit Complexity
Polynomial-Time Isomorphism
Probabilistic Complexity
Probabilistic Machines and Complexity Classes
Complexity of Counting
Interactive Proof Systems
Probabilistically Checkable Proofs and NP-Hard