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This new text offers a comprehensive and accessible treatment of the theory of algorithms and complexity - the elegant body of concepts and methods developed by computer scientists over the past 30 years for studying the performance and li, Computational Complexity4 out of 5 stars based on 2 reviews
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Book Categories |
| Pt. I | Algorithms | 1 |
| 1 | Problems and Algorithms | 3 |
| 2 | Turing machines | 19 |
| 3 | Computability | 57 |
| Pt. II | Logic | 71 |
| 4 | Boolean logic | 73 |
| 5 | First-order logic | 87 |
| 6 | Undecidability in logic | 123 |
| Pt. III | P and NP | 137 |
| 7 | Relations between complexity classes | 139 |
| 8 | Reductions and completeness | 159 |
| 9 | NP-complete problems | 181 |
| 10 | coNP and function problems | 219 |
| 11 | Randomized computation | 241 |
| 12 | Cryptography | 279 |
| 13 | Approximability | 299 |
| 14 | On P vs. NP | 329 |
| Pt. IV | Inside P | 357 |
| 15 | Parallel computation | 359 |
| 16 | Logarithmic space | 395 |
| Pt. V | Beyond NP | 409 |
| 17 | The polynomial hierarchy | 411 |
| 18 | Computation that counts | 439 |
| 19 | Polynomial space | 455 |
| 20 | A glimpse beyond | 491 |
| Index | 509 | |
| Author index | 519 |
| Price | Condition | Delivery | Seller | Action |
| $107.19 | Digital |
| WonderClub |
David Votaw
reviewed Computational Complexity on June 14, 2020 Computational Complexity
If you read this book as first time in order to understand Computational Complexity, then you're probably not going to like it. You need to read Sipser's textbook before you read this book and make sure that you have a strong background in discrete mathematics (if not, then see Rosen's textbook in Discrete Mathematics). This book is recommended by best people in complexity and algorithms such as Scott Aaronson, Sipser, etc. You need to solve as many exercises as you go.
The book has five parts:
Part I: Algorithms
Part II: Logic
Part III: P and NP
Part IV: Inside P
Part V: Beyond NP
The most important parts are in Part I, III.
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