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El. knyga: Turing's Vision: The Birth of Computer Science

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  • Formatas: 208 pages
  • Serija: Turing's Vision
  • Išleidimo metai: 13-May-2016
  • Leidėjas: MIT Press
  • Kalba: eng
  • ISBN-13: 9780262333801
  • Formatas: 208 pages
  • Serija: Turing's Vision
  • Išleidimo metai: 13-May-2016
  • Leidėjas: MIT Press
  • Kalba: eng
  • ISBN-13: 9780262333801

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In 1936, when he was just twenty-four years old, Alan Turing wrote a remarkable paper in which he outlined the theory of computation, laying out the ideas that underlie all modern computers. This groundbreaking and powerful theory now forms the basis of computer science. In Turing's Vision, Chris Bernhardt explains the theory, Turing's most important contribution, for the general reader. Bernhardt argues that the strength of Turing's theory is its simplicity, and that, explained in a straightforward manner, it is eminently understandable by the nonspecialist. As Marvin Minsky writes, "The sheer simplicity of the theory's foundation and extraordinary short path from this foundation to its logical and surprising conclusions give the theory a mathematical beauty that alone guarantees it a permanent place in computer theory." Bernhardt begins with the foundation and systematically builds to the surprising conclusions. He also views Turing's theory in the context of mathematical history, other views of computation (including those of Alonzo Church), Turing's later work, and the birth of the modern computer.

In the paper, "On Computable Numbers, with an Application to the Entscheidungsproblem," Turing thinks carefully about how humans perform computation, breaking it down into a sequence of steps, and then constructs theoretical machines capable of performing each step. Turing wanted to show that there were problems that were beyond any computer's ability to solve; in particular, he wanted to find a decision problem that he could prove was undecidable. To explain Turing's ideas, Bernhardt examines three well-known decision problems to explore the concept of undecidability; investigates theoretical computing machines, including Turing machines; explains universal machines; and proves that certain problems are undecidable, including Turing's problem concerning computable numbers.

Acknowledgments ix
Introduction xi
1 Background
1(14)
Mathematical Certainty
2(2)
Boole's Logic
4(1)
Mathematical Logic
5(2)
Securing the Foundations of Mathematics
7(1)
Hilbert's Approach
8(2)
Godel's Results
10(1)
Turing's Results
11(4)
2 Some Undecidable Decision Problems
15(10)
Emil Post
16(1)
Post's Correspondence Problem
17(5)
Hilbert's Tenth Problem
22(2)
The Halting Problem
24(1)
Back to Turing at Cambridge
24(1)
3 Finite Automata
25(22)
Introduction
25(2)
Finite Automata
27(1)
Our First Machine
27(2)
Alphabets and Languages
29(2)
Finite Automata and Answering Questions
31(2)
Omitting Traps from Diagrams
33(2)
Some Basic Facts
35(2)
Regular Expressions
37(4)
Limitations of Finite Automata
41(2)
Tapes and Configurations
43(1)
Connection to the Correspondence Problem
44(3)
4 Turing Machines
47(22)
Examples of Turing Machines
52(7)
Computable Functions and Calculations
59(2)
Church-Turing Thesis
61(2)
Computational Power
63(4)
Machines That Don't Halt
67(2)
5 Other Systems for Computation
69(18)
The Lambda Calculus
72(7)
Tag Systems
79(3)
One-Dimensional Cellular Automata
82(5)
6 Encodings and the Universal Machine
87(20)
A Method of Encoding Finite Automata
88(3)
Universal Machines
91(2)
Construction of Universal Machines
93(2)
Modern Computers Are Universal Machines
95(2)
Von Neumann Architecture
97(1)
Random Access Machines
98(3)
RAMs Can Be Emulated by Turing Machines
101(2)
Other Universal Machines
103(1)
What Happens When We Input (M) into M?
104(3)
7 Undecidable Problems
107(16)
Proof by Contradiction
108(3)
Russell's Barber
111(2)
Finite Automata That Do Not Accept Their Encodings
113(1)
Turing Machines That Do Not Accept Their Encodings
114(2)
Does a Turing Machine Diverge on Its Encoding? Is Undecidable
116(1)
The Acceptance, Halting, and Blank Tape Problems
117(2)
An Uncomputable Function
119(1)
Turing's Approach
120(3)
8 Cantor's Diagonalization Arguments
123(24)
Georg Cantor 1845--1918
123(1)
Cardinality
124(2)
Subsets of the Rationals That Have the Same Cardinality
126(3)
Hilbert's Hotel
129(2)
Subtraction Is Not Well-Defined
131(1)
General Diagonal Argument
131(4)
The Cardinality of the Real Numbers
135(3)
The Diagonal Argument
138(1)
The Continuum Hypothesis
139(1)
The Cardinality of Computations
140(1)
Computable Numbers
141(1)
A Non-Computable Number
142(1)
There Is a Countable Number of Computable Numbers
143(1)
Computable Numbers Are Not Effectively Enumerable
143(4)
9 Turing's Legacy
147(16)
Turing at Princeton
148(2)
Second World War
150(3)
Development of Computers in the 1940s
153(4)
The Turing Test
157(2)
Downfall
159(2)
Apology and Pardon
161(2)
Further Reading 163(4)
Notes 167(16)
Bibliography 183(4)
Index 187