Complexity theory is a central field of the theoretical foundations of computer science. It is concerned with the general study of the intrinsic complexity of computational tasks; that is, it addresses the question of what can be achieved within limited time (and/or with other limited natural computational resources). This book offers a conceptual perspective on complexity theory. It is intended to serve as an introduction for advanced undergraduate and graduate students, either as a textbook or for self-study. The book will also be useful to experts, since it provides expositions of the various sub-areas of complexity theory such as hardness amplification, pseudorandomness and probabilistic proof systems. In each case, the author starts by posing the intuitive questions that are addressed by the sub-area and then discusses the choices made in the actual formulation of these questions, the approaches that lead to the answers, and the ideas that are embedded in these answers.
• Presents a conceptual perspective, meaning the text evolves around the underlying intuitive questions on the subject • The focus is on motivation and ideas • Organized around conceptual themes
Contents
1. Introduction and preliminaries; 2. P, NP and NP-completeness; 3. Variations on P and NP; 4. More resources, more power?; 5. Space complexity; 6. Randomness and counting; 7. The bright side of hardness; 8. Pseudorandom generators; 9. Probabiistic proof systems; 10. Relaxing the requirements; Epilogue; A. Glossary of complexity classes; B. On the quest for lower bounds; C. On the foundations of modern cryptography; D. Probabilistic preliminaries and advanced topics in randomization; E. Explicit constructions; F. Some omitted proofs; G. Some computational problems.
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