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Theory of computational complexity

Title
Theory of computational complexity / Ding-Zhu Du, Department of Computer Science, University of Texas at Dallas, Ann Arbor, MI, Ker-I Ko, Department of Computer Science, State University of New York at Stony Brook, Stony Brook, NY.
ISBN
9781118593035 (electronic bk.)
1118593030 (electronic bk.)
9781118306086 (cloth)
1118306082 (cloth)
Edition
Second edition.
Publication
Hoboken, New Jersey : John Wiley & Sons, Inc., [2014]
Copyright Notice Date
©2014
Physical Description
1 online resource ( 514 pages)
Local Notes
Access is available to the Yale community.
Notes
Description based upon print version of record.
Historical Notes
Electronic reproduction. Palo Alto, Calif. Available via World Wide Web.
Access and use
Access restricted by licensing agreement.
Other formats
Print version: Du, Ding-Zhu. Theory of Computational Complexity. 2nd ed. Hoboken : Wiley, 2014
Format
Books / Online
Language
English
Added to Catalog
June 17, 2014
Series
Wiley series in discrete mathematics and optimization.
Wiley Series in Discrete Mathematics and Optimization
Bibliography
Includes bibliographical references and index.
Contents
Cover; Title Page; Contents; Preface; Notes on the Second Edition; Part I Uniform Complexity; Chapter 1 Models of Computation and Complexity Classes; 1.1 Strings, Coding, and Boolean Functions; 1.2 Deterministic Turing Machines; 1.3 Nondeterministic Turing Machines; 1.4 Complexity Classes; 1.5 Universal Turing Machine; 1.6 Diagonalization; 1.7 Simulation; Exercises; Historical Notes; Chapter 2 NP-Completeness; 2.1 NP; 2.2 Cook's Theorem; 2.3 More NP-Complete Problems; 2.4 Polynomial-Time Turing Reducibility; 2.5 NP-Complete Optimization Problems; Exercises; Historical Notes
Chapter 3 The Polynomial-Time Hierarchy and Polynomial Space3.1 Nondeterministic Oracle Turing Machines; 3.2 Polynomial-Time Hierarchy; 3.3 Complete Problems in PH; 3.4 Alternating Turing Machines; 3.5 PSPACE-Complete Problems; 3.6 EXP-Complete Problems; Exercises; Historical Notes; Chapter 4 Structure of NP; 4.1 Incomplete Problems in NP; 4.2 One-Way Functions and Cryptography; 4.3 Relativization; 4.4 Unrelativizable Proof Techniques; 4.5 Independence Results; 4.6 Positive Relativization; 4.7 Random Oracles; 4.8 Structure of Relativized NP; Exercises; Historical Notes
Part II Nonuniform ComplexityChapter 5 Decision Trees; 5.1 Graphs and Decision Trees; 5.2 Examples; 5.3 Algebraic Criterion; 5.4 Monotone Graph Properties; 5.5 Topological Criterion; 5.6 Applications of the Fixed Point Theorems; 5.7 Applications of Permutation Groups; 5.8 Randomized Decision Trees; 5.9 Branching Programs; Exercises; Historical Notes; Chapter 6 Circuit Complexity; 6.1 Boolean Circuits; 6.2 Polynomial-Size Circuits; 6.3 Monotone Circuits; 6.4 Circuits with Modulo Gates; 6.5 NC; 6.6 Parity Function; 6.7 P-Completeness; 6.8 Random Circuits and RNC; Exercises; Historical Notes
Chapter 7 Polynomial-Time Isomorphism7.1 Polynomial-Time Isomorphism; 7.2 Paddability; 7.3 Density of NP-Complete Sets; 7.4 Density of EXP-Complete Sets; 7.5 One-Way Functions and Isomorphism in EXP; 7.6 Density of P-Complete Sets; Exercises; Historical Notes; Part III Probabilistic Complexity; Chapter 8 Probabilistic Machines and Complexity Classes; 8.1 Randomized Algorithms; 8.2 Probabilistic Turing Machines; 8.3 Time Complexity of Probabilistic Turing Machines; 8.4 Probabilistic Machines with Bounded Errors; 8.5 BPP and P; 8.6 BPP and NP; 8.7 BPP and the Polynomial-Time Hierarchy
8.8 Relativized Probabilistic Complexity ClassesExercises; Historical Notes; Chapter 9 Complexity of Counting; 9.1 Counting Class #P; 9.2 #P-Complete Problems; 9.3 oplus P and the Polynomial-Time Hierarchy; 9.4 #P and the Polynomial-Time Hierarchy; 9.5 Circuit Complexity and Relativized oplus P and #P; 9.6 Relativized Polynomial-Time Hierarchy; Exercises; Historical Notes; Chapter 10 Interactive Proof Systems; 10.1 Examples and Definitions; 10.2 Arthur-Merlin Proof Systems; 10.3 AM Hierarchy Versus Polynomial-Time Hierarchy; 10.4 IP Versus AM; 10.5 IP Versus PSPACE; Exercises
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