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.

Includes bibliographical references and index.

Print version record and CIP data provided by publisher.

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.

Praise for the First Edition "" ... complete, up-to-date coverage of computational complexity theory ... the book promises to become the standard reference on computational complexity.""--Zentralblatt MATH 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.