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Weak Intelligence: Through the Principle and Paradox of Multiple Knowledge

Matjaz Gams
Format
Book
Published
Huntington, N.Y. : Nova Science, c2001.
Language
English
Series
Advances in Computation
ISBN
1560728981
Contents
  • Chapter 1 Artificial Intelligence 1
  • 1.1 Artificial Intelligence Direction 1
  • 1.2 History of Artificial Intelligence 2
  • 1.3 Where's the AI? 5
  • 1.4 Storage/Memory vs. Processing/Thinking 15
  • 1.5 Problems with Formalistic AI 17
  • 1.6 Strong-AI Super-Projects 28
  • Chapter 2 Trends of Computer Progress 35
  • 2.1 Short History of Computing 35
  • 2.2 Trends of Hardware Progress 38
  • 2.3 Software Evolution 42
  • 2.4 Near Future 44
  • 2.5 Trends of Computer Progress 46
  • 2.6 Practical Implications of Computer Progress 46
  • 2.7 Mass Memory - a Possible Break-Through 48
  • 2.8 Exponential Growth Leads to Explosion 50
  • Chapter 3 Brain 53
  • 3.1 Our History and Future - the Human 53
  • 3.2 Brains and Minds 57
  • 3.3 Neural Darwinism 68
  • 3.4 Cognitive Sciences 73
  • 3.5 Arizona Science of Consciousness 74
  • 3.6 Brain is the Most Complex System in Our Universe 81
  • Chapter 4 Strong Versus Weak AI 83
  • 4.1 Description 83
  • 4.2 Sloman's Engineering Gradation of Strong-Weak AI 84
  • Chapter 5 Fundamentals of AI, Computer Science, and Science in General 87
  • 5.1 Alan Turing 87
  • 5.2 Turing Test 88
  • 5.3 Turning Machine and Church-Turing Thesis 91
  • 5.4 Church-Turing Thesis and Turing Machines 95
  • 5.5 Godel's Theorem and the Halting Problem 98
  • 5.6 Penrose's Analyses of Godel's Theorem 104
  • 5.7 Is Interaction Stronger Than Algorithms? 120
  • Chapter 6 Principle and Paradox of Multiple Knowledge 125
  • 6.1 Basic Definitions 125
  • 6.2 Principle of Multiple Knowledge 129
  • 6.3 Paradox of Multiple Knowledge 131
  • Chapter 7 Confirmations of the Principle 135
  • 7.1 Multiple Knowledge in Empirical Learning 136
  • 7.2 Simulated Multiple Models 159
  • 7.3 Formal Worst-Case Analyses 167
  • 7.4 Formal Average-Case Improvements 167
  • 7.5 Fitting the Model to Real-Life Applications 187
  • 7.6 Human Multiple Reasoning 196
  • 7.7 Cognitive Sciences and Common Sense 198
  • Chapter 8 Consequences 201
  • 8.1 Occam's Razor vs. Multiple Knowledge 201
  • 8.2 Bayes' Classifier and Multiple Knowledge 203
  • 8.3 Properties of Knowledge 204
  • Chapter 9 Many-Worlds Theory and Quantum Computing 209
  • 9.1 Paradoxes of Modern Physics 209
  • 9.2 Interpretations of Quantum Physics 210
  • 9.3 Many-Worlds Theory 210
  • 9.4 Objections to the Multiple-World Interpretation 211
  • 9.5 Quantum Computing 212
  • 9.6 From Many Worlds to the Principle of Multiple Knowledge 214
  • Chapter 10 Strong AI Fights Back 217.
Description
xix, 245 p. : ill. ; 26 cm.
Notes
Includes bibliographical references (p. 225-242) and index.
Series Statement
Advances in computation. Theory and parctice ; v. 6
Technical Details
  • Access in Virgo Classic
  • Staff View

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    g| Chapter 1 t| Artificial Intelligence g| 1 -- g| 1.1 t| Artificial Intelligence Direction g| 1 -- g| 1.2 t| History of Artificial Intelligence g| 2 -- g| 1.3 t| Where's the AI? g| 5 -- g| 1.4 t| Storage/Memory vs. Processing/Thinking g| 15 -- g| 1.5 t| Problems with Formalistic AI g| 17 -- g| 1.6 t| Strong-AI Super-Projects g| 28 -- g| Chapter 2 t| Trends of Computer Progress g| 35 -- g| 2.1 t| Short History of Computing g| 35 -- g| 2.2 t| Trends of Hardware Progress g| 38 -- g| 2.3 t| Software Evolution g| 42 -- g| 2.4 t| Near Future g| 44 -- g| 2.5 t| Trends of Computer Progress g| 46 -- g| 2.6 t| Practical Implications of Computer Progress g| 46 -- g| 2.7 t| Mass Memory - a Possible Break-Through g| 48 -- g| 2.8 t| Exponential Growth Leads to Explosion g| 50 -- g| Chapter 3 t| Brain g| 53 -- g| 3.1 t| Our History and Future - the Human g| 53 -- g| 3.2 t| Brains and Minds g| 57 -- g| 3.3 t| Neural Darwinism g| 68 -- g| 3.4 t| Cognitive Sciences g| 73 -- g| 3.5 t| Arizona Science of Consciousness g| 74 -- g| 3.6 t| Brain is the Most Complex System in Our Universe g| 81 -- g| Chapter 4 t| Strong Versus Weak AI g| 83 -- g| 4.1 t| Description g| 83 -- g| 4.2 t| Sloman's Engineering Gradation of Strong-Weak AI g| 84 -- g| Chapter 5 t| Fundamentals of AI, Computer Science, and Science in General g| 87 -- g| 5.1 t| Alan Turing g| 87 -- g| 5.2 t| Turing Test g| 88 -- g| 5.3 t| Turning Machine and Church-Turing Thesis g| 91 -- g| 5.4 t| Church-Turing Thesis and Turing Machines g| 95 -- g| 5.5 t| Godel's Theorem and the Halting Problem g| 98 -- g| 5.6 t| Penrose's Analyses of Godel's Theorem g| 104 -- g| 5.7 t| Is Interaction Stronger Than Algorithms? g| 120 -- g| Chapter 6 t| Principle and Paradox of Multiple Knowledge g| 125 -- g| 6.1 t| Basic Definitions g| 125 -- g| 6.2 t| Principle of Multiple Knowledge g| 129 -- g| 6.3 t| Paradox of Multiple Knowledge g| 131 -- g| Chapter 7 t| Confirmations of the Principle g| 135 -- g| 7.1 t| Multiple Knowledge in Empirical Learning g| 136 -- g| 7.2 t| Simulated Multiple Models g| 159 -- g| 7.3 t| Formal Worst-Case Analyses g| 167 -- g| 7.4 t| Formal Average-Case Improvements g| 167 -- g| 7.5 t| Fitting the Model to Real-Life Applications g| 187 -- g| 7.6 t| Human Multiple Reasoning g| 196 -- g| 7.7 t| Cognitive Sciences and Common Sense g| 198 -- g| Chapter 8 t| Consequences g| 201 -- g| 8.1 t| Occam's Razor vs. Multiple Knowledge g| 201 -- g| 8.2 t| Bayes' Classifier and Multiple Knowledge g| 203 -- g| 8.3 t| Properties of Knowledge g| 204 -- g| Chapter 9 t| Many-Worlds Theory and Quantum Computing g| 209 -- g| 9.1 t| Paradoxes of Modern Physics g| 209 -- g| 9.2 t| Interpretations of Quantum Physics g| 210 -- g| 9.3 t| Many-Worlds Theory g| 210 -- g| 9.4 t| Objections to the Multiple-World Interpretation g| 211 -- g| 9.5 t| Quantum Computing g| 212 -- g| 9.6 t| From Many Worlds to the Principle of Multiple Knowledge g| 214 -- g| Chapter 10 t| Strong AI Fights Back g| 217.
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    a| Q335 .G354 2001 w| LC i| X004522913 l| STACKS m| SCI-ENG t| BOOK
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