دسترسی نامحدود
برای کاربرانی که ثبت نام کرده اند
برای ارتباط با ما می توانید از طریق شماره موبایل زیر از طریق تماس و پیامک با ما در ارتباط باشید
در صورت عدم پاسخ گویی از طریق پیامک با پشتیبان در ارتباط باشید
برای کاربرانی که ثبت نام کرده اند
درصورت عدم همخوانی توضیحات با کتاب
از ساعت 7 صبح تا 10 شب
ویرایش:
نویسندگان: Rod Downey
سری: Undergraduate Topics in Computer Science
ISBN (شابک) : 9783031537431, 9783031537448
ناشر: Springer
سال نشر: 2024
تعداد صفحات: 361
زبان: English
فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود)
حجم فایل: 4 مگابایت
در صورت تبدیل فایل کتاب Computability and Complexity. Foundations and Tools for Pursuing Scientific Applications به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب قابلیت محاسبه و پیچیدگی مبانی و ابزارهای پیگیری کاربردهای علمی نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
Preface Acknowledgements Introduction Contents Part I Background Chapter 1 Some Naive Set Theory 1.1 Introduction 1.1.1 Basic definitions 1.1.2 Countable sets 1.2 Gödel numberings and other coding techniques 1.2.1 Exercises 1.3 Diagonalization and Uncountable Sets 1.3.1 Exercises 1.4 Set Theory in Mathematics 1.4.1 The Cardinality of a Set and the Continuum Hypothesis* Part II Computability Theory Chapter 2 Regular Languages and Finite Automata 2.1 Introduction 2.2 Regular Languages 2.2.1 Formal languages 2.2.2 Regular expressions and languages 2.2.3 The Pumping Lemma 2.2.4 Exercises 2.2.5 Closure properties of regular languages 2.3 Finite State Automata 2.3.1 Deterministic Finite Automata 2.4 Exercises 2.4.1 Nondeterministic Finite Automata 2.4.2 The Rabin-Scott Theorem 2.4.3 Exercises 2.4.4 Nondeterministic automata with ⋋-moves 2.5 Exercises 2.6 Kleene\'s Theorem: Finite State = Regular 2.6.1 Historical Notes 2.7 The Myhill-Nerode Theorem* 2.7.1 The Method of Test Sets 2.7.2 State Minimization* 2.7.3 Exercises 2.7.4 Historical Notes Chapter 3 General Models of Computation 3.1 Introduction 3.2 Turing Machines 3.2.1 Exercises 3.2.2 Coding, Gödel numbering and other domains beside N 3.2.3 Exercises 3.2.4 The Church-Turing Thesis 3.2.5 Nondeterminism 3.2.6 A Universal Turing machine 3.3 Partial recursive functions 3.3.1 Primitive recursive functions 3.3.2 Exercises 3.3.3 Primitive Recursive Relations 3.3.4 Bounded quantification 3.3.5 Exercises 3.3.6 Partial recursive functions 3.3.7 Gödel Numbering Turing Computations 3.3.8 The Kleene Normal Form Theorem 3.4 Minsky and Register Machines 3.4.1 Exercises Chapter 4 Undecidable Problems 4.1 Introduction 4.1.1 Exercises 4.1.2 The Halting Problem 4.1.3 Exercises 4.2 Minsky Machines and Generalized Collatz Functions 4.2.1 Collatz functions 4.2.2 Vector games 4.2.3 Rational Games 4.2.4 Generalized Collatz functions 4.2.5 Exercises 4.3 Unsolvable Word problems 4.3.1 Semi-Thue Processes 4.3.2 Thue Processes and Word Problems in Semigroups 4.3.3 Exercises 4.3.4 Post\'s correspondence problem 4.3.5 Groups* 4.3.6 The Entscheidungsproblem* 4.3.7 Diophantine equations* 4.3.8 Exercises 4.3.9 Coda Chapter 5 Deeper Computability 5.1 Introduction 5.1.1 Computably Enumerable Sets 5.1.2 Exercises 5.1.3 The s-m-n Theorem 5.2 Index Sets and Rice\'s Theorem 5.3 The Recursion Theorem 5.3.1 An Alternative Proof of the Recursion Theorem* 5.3.2 Exercises 5.4 Wait and See Arguments 5.4.1 Some Examples 5.4.2 Computable Structure Theory: Computable Linear Orderings 5.4.3 Exercises 5.5 Turing Reducibility 5.5.1 Oracle machines and Turing reducibility 5.5.2 Universal Oracle Machines 5.5.3 Use functions 5.5.4 The jump operator 5.6 The Arithmetic Hierarchy 5.6.1 The Limit Lemma 5.6.2 Exercises 5.6.3 Post\'s Theorem 5.6.4 Exercises 5.7 The Structure of Turing Degrees and Post\'s Problem 5.7.1 Exercises 5.7.2 Post\'s Problem and the Finite Injury Priority Method 5.7.3 Exercises 5.7.4 Sacks\' Splitting Theorem* 5.7.5 Exercises Part III Computational Complexity Theory Chapter 6 Computational Complexity 6.1 Introduction 6.1.1 Size matters 6.1.2 The Basic Model 6.1.3 Discussion and Basic Definitions 6.1.4 Exercises 6.1.5 Polynomial Time and Space 6.1.6 Universal Enumerations 6.1.7 Using Clocks 6.1.8 Hierarchy Theorems 6.1.9 Exercises 6.2 Blum\'s Speedup Theorem 6.3 The Union Theorem* Chapter 7 NP- and PSPACE-Completeness 7.1 The Polynomial Time Hierarchy 7.2 NP Completeness 7.2.1 Machine NP-Complete Problems 7.2.2 Exercises 7.2.3 The Cook-Levin Theorem 7.2.4 Search vs Decision Problems: Polynomial Time Turing Reductions 7.2.5 Exercises 7.2.6 Some Natural NP-Complete Problems 7.2.7 Exercises 7.2.8 More NP-Completeness 7.2.9 Exercises 7.2.10 Even More NP-Completeness 7.2.11 Commentary* 7.2.12 Exercises 7.3 Space 7.3.1 Savitch\'s Theorem 7.3.2 Time vs Space 7.3.3 Exercises 7.4 Natural PSPACE-Complete Problems 7.4.1 Exercises 7.5 Further Variations on the Theme : Advice Classes and Randomized Reductions 7.5.1 Introduction 7.5.2 Advice and Nonuniform Complexity Classes 7.5.3 Valiant-Vazirani and BPP Chapter 8 Some Structural Complexity 8.1 Introduction 8.1.1 Oracles 8.1.2 Exercises 8.1.3 The Role of Oracles and Other Indications that We Don\'t Know How to Approach P vs NP 8.2 Polynomial Time Degrees and Ladner\'s Theorem 8.2.1 Exercises Chapter 9 Parameterized Complexity 9.1 Introduction 9.2 Formal Definitions 9.2.1 Discussion 9.3 Parametric Intractability 9.3.1 A basic hardness class: W[1] 9.3.2 Exercises 9.3.3 The W-hierarchy 9.3.4 Showing Known Algorithms are Likely Very Bad Indeed; Especially in PTAS\'s 9.4 Parameterized Tractability 9.4.1 Bounded Search Trees 9.4.2 Exercises 9.4.3 Kernelization 9.4.4 Exercises 9.4.5 Iterative Compression 9.4.6 Exercises 9.4.7 Not-Quite-Practical FPT Algorithms* 9.4.8 Exercises 9.5 Kernelization Lower Bounds 9.5.1 Exercises 9.6 Another Basic Hardness Class and XP Optimality* 9.6.1 Exercises Chapter 10 Other Approaches to Coping with Hardness* 10.1 Introduction 10.2 Approximation Algorithms 10.2.1 Constant Distance Approximation 10.2.2 Exercises 10.2.3 Constant Approximation Ratios 10.2.4 APX Completeness 10.2.5 Exercises 10.2.6 PTAS\'s 10.2.7 Parameterized Approximation 10.2.8 Parameterized Inapproximability 10.2.9 Exercises 10.3 Average Case Complexity 10.3.1 Polynomial Time on Average 10.3.2 DistNP 10.3.3 Livne\'s ``Natural\'\' Average Case Complete Problems 10.3.4 Exercises 10.4 Generic Case Complexity 10.4.1 Basic Definitions 10.4.2 Exercises 10.5 Smoothed Analysis 10.6 Summary Part IV Selected Solutions to Exercises Chapter 11 Solutions 11.1 Chapter 1 11.2 Chapter 2 11.3 Chapter 3 11.4 Chapter 5 11.5 Chapter 6 11.6 Chapter 7 11.7 Chapter 8 11.8 Chapter 9 11.9 Chapter 10 References Index