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Artificial Intelligence with Uncertainty

   این کتاب  من دارم خواستین بفرستم 

Contents

Chapter 1

The 50-Year History of Artificial Intelligence ....................................1

1.1 Departure from the Dartmouth Symposium....................................................1

1.1.1 Communication between Different Disciplines...................................1

1.1.2 Development and Growth ....................................................................3

1.2 Expected Goals as Time Goes On...................................................................4

1.2.1 Turing Test ...........................................................................................4

1.2.2 Machine Theorem Proof ......................................................................5

1.2.3 Rivalry between Kasparov and Deep Blue .........................................5

1.2.4 Thinking Machine ................................................................................6

1.2.5 Artificial Life........................................................................................7

1.3 AI Achievements in 50 Years...........................................................................8

1.3.1 Pattern Recognition..............................................................................8

1.3.2 Knowledge Engineering.....................................................................10

1.3.3 Robotics..............................................................................................11

1.4 Major Development of AI in the Information Age .......................................12

1.4.1 Impacts of AI Technology on the Whole Society .............................12

1.4.2 From the World Wide Web to the Intelligent Grid ...........................13

1.4.3 From Data to Knowledge ..................................................................14

1.5 The Cross Trend between AI, Brain Science and Cognitive Science...........15

1.5.1 The Influence of Brain Science on AI...............................................15

1.5.2 The Influence of Cognitive Science on AI........................................17

1.5.3 Coming Breakthroughs Caused by Interdisciplines ..........................18

References................................................................................................................18

Chapter 2

Methodologies of AI ..........................................................................21

2.1 Symbolism Methodology...............................................................................21

2.1.1 Birth and Development of Symbolism .............................................21

2.1.2 Predicate Calculus and Resolution Principle ....................................24

2.1.3 Logic Programming Language ..........................................................26

2.1.4 Expert System ....................................................................................28

2.2 Connectionism Methodology.........................................................................30

2.2.1 Birth and Development of Connectionism ........................................30

2.2.2 Strategy and Technical Characteristics of Connectionism................30

2.2.3 Hopfield Neural Network Model.......................................................33

2.2.4 Back-Propagation Neural Network Model ........................................34

2.3 Behaviorism Methodology.............................................................................35

2.3.1 Birth and Development of Behaviorism............................................35

2.3.2 Robot Control.....................................................................................36

2.3.3 Intelligent Control ..............................................................................37

2.4 Reflection on Methodologies .........................................................................38

References................................................................................................................39

Chapter 3

On Uncertainties of Knowledge ........................................................43

3.1 On Randomness .............................................................................................43

3.1.1 The Objectivity of Randomness ....................................................... 43

3.1.2 The Beauty of Randomness...............................................................46

3.2 On Fuzziness ..................................................................................................47

3.2.1 The Objectivity of Fuzziness .............................................................48

3.2.2 The Beauty of Fuzziness ...................................................................49

3.3 Uncertainties in Natural Languages ..............................................................51

3.3.1 Languages as the Carrier of Human Knowledge ..............................51

3.3.2 Uncertainties in Languages................................................................52

3.4 Uncertainties in Commonsense Knowledge..................................................54

3.4.1 Common Understanding about Common Sense ...............................54

3.4.2 Relativity of Commonsense Knowledge ...........................................55

3.5 Other Uncertainties of Knowledge ................................................................57

3.5.1 Incompleteness of Knowledge...........................................................57

3.5.2 Incoordination of Knowledge ............................................................58

3.5.3 Impermanence of Knowledge............................................................58

References................................................................................................................60

Chapter 4

Mathematical Foundation of AI with Uncertainty ............................61

4.1 Probability Theory .........................................................................................61

4.1.1 Bayes’ Theorem .................................................................................62

4.1.1.1 Relationship and Logical Operation

of Random Event................................................................62

4.1.1.2 Axiomization Definition of Probability .............................63

4.1.1.3 Conditional Probability and Bayes’ Theorem....................64

4.1.2 Probability Distribution Function ......................................................65

4.1.3 Normal Distribution ...........................................................................67

4.1.3.1 The Definition and Properties

of Normal Distribution .......................................................67

4.1.3.2 Multidimensional Normal Distribution ..............................69

4.1.4 Laws of Large Numbers and Central Limit Theorem.......................70

4.1.4.1 Laws of Large Numbers.....................................................70

4.1.4.2 Central Limit Theorem .......................................................71

4.1.5 Power Law Distribution .....................................................................73

4.1.6 Entropy ...............................................................................................74

4.2 Fuzzy Set Theory ...........................................................................................76

4.2.1 Membership Degree and Membership Function ...............................76

4.2.2 Decomposition Theorem and Expanded Principle............................78

4.2.3 Fuzzy Relation ...................................................................................79

4.2.4 Possibility Measure ............................................................................81

4.3 Rough Set Theory ..........................................................................................81

4.3.1 Imprecise Category and Rough Set ...................................................82

4.3.2 Characteristics of Rough Sets............................................................84

4.3.3 Rough Relations.................................................................................86

4.4 Chaos and Fractal...........................................................................................89

4.4.1 Basic Characteristics of Chaos ..........................................................90

4.4.2 Strange Attractors of Chaos...............................................................92

4.4.3 Geometric Characteristics of Chaos and Fractal...............................93

4.5 Kernel Functions and Principal Curves.........................................................94

4.5.1 Kernel Functions ................................................................................94

4.5.2 Support Vector Machine.....................................................................97

4.5.3 Principal Curves ...............................................................................100

References..............................................................................................................104

Chapter 5

Qualitative and Quantitative Transform

Model — Cloud Model ...................................................................107

5.1 Perspectives on the Study of AI with Uncertainty......................................107

5.1.1 Multiple Perspectives on the Study

of Human Intelligence .....................................................................107

5.1.2 The Importance of Concepts in Natural Languages .......................110

5.1.3 The Relationship between Randomness and Fuzziness

in a Concept .....................................................................................110

5.2 Representing Concepts Using Cloud Models..............................................112

5.2.1 Cloud and Cloud Drop.....................................................................112

5.2.2 Numerical Characteristics of Cloud ................................................113

5.2.3 Types of Cloud Model .....................................................................115

5.3 Normal Cloud Generator .............................................................................118

5.3.1 Forward Cloud Generator ................................................................118

5.3.2 Contributions of Cloud Drops to a Concept ...................................123

5.3.3 Understanding the Lunar Calendar’s Solar Terms

through Cloud Models .....................................................................124

5.3.4 Backward Cloud Generator .............................................................125

5.3.5 Precision Analysis of Backward Cloud Generator..........................132

5.3.6 More on Understanding Normal Cloud Model ...............................133

5.4 Mathematical Properties of Normal Cloud .................................................138

5.4.1 Statistical Analysis of the Cloud Drops’ Distribution.....................138

5.4.2 Statistical Analysis of the Cloud Drops’

Certainty Degree ..............................................................................140

5.4.3 Expectation Curves of Normal Cloud .............................................142

5.5 On the Pervasiveness of the Normal Cloud Model.....................................144

5.5.1 Pervasiveness of Normal Distribution .............................................144

5.5.2 Pervasiveness of Bell Membership Function ..................................145

5.5.3 Significance of Normal Cloud .........................................................148

References..............................................................................................................150

Chapter 6

Discovering Knowledge with Uncertainty

through Methodologies in Physics ..................................................153

6.1 From Perception of Physical World to Perception of Human Self ............153

6.1.1 Expressing Concepts by Using Atom Models.................................154

6.1.2 Describing Interaction between Objects by Using Field ................155

6.1.3 Describing Hierarchical Structure of Knowledge

by Using Granularity .......................................................................156

6.2 Data Field.....................................................................................................158

6.2.1 From Physical Field to Data Field ..................................................158

6.2.2 Potential Field and Force Field of Data ..........................................160

6.2.3 Influence Coefficient Optimization of Field Function ....................172

6.2.4 Data Field and Visual Thinking Simulation ....................................178

6.3 Uncertainty in Concept Hierarchy...............................................................182

6.3.1 Discretization of Continuous Data ..................................................183

6.3.2 Virtual Pan Concept Tree.................................................................186

6.3.3 Climbing-Up Strategy and Algorithms............................................188

6.4 Knowledge Discovery State Space ..............................................................196

6.4.1 Three Kinds of State Spaces............................................................196

6.4.2 State Space Transformation .............................................................197

6.4.3 Major Operations in State Space Transformation ...........................199

References..............................................................................................................200

Chapter 7

Data Mining for Discovering Knowledge with Uncertainty...........201

7.1 Uncertainty in Data Mining.........................................................................201

7.1.1 Data Mining and Knowledge Discovery .........................................201

7.1.2 Uncertainty in Data Mining Process ...............................................202

7.1.3 Uncertainty in Discovered Knowledge............................................204

7.2 Classification and Clustering with Uncertainty...........................................205

7.2.1 Cloud Classification .........................................................................206

7.2.2 Clustering Based on Data Field.......................................................213

7.2.3 Outlier Detection and Discovery Based on Data Field...................238

7.3 Discovery of Association Rules with Uncertainty ......................................244

7.3.1 Reconsideration of the Traditional Association Rules ....................244

7.3.2 Association Rule Mining and Forecasting ......................................247

7.4 Time Series Data Mining and Forecasting..................................................253

7.4.1 Time Series Data Mining Based on Cloud Models ........................255

7.4.2 Stock Data Forecasting ....................................................................256

References..............................................................................................................269

Chapter 8

Reasoning and Control of Qualitative Knowledge .........................273

8.1 Qualitative Rule Construction by Cloud .....................................................273

8.1.1 Precondition Cloud Generator and Postcondition

Cloud Generator...............................................................................273

8.1.2 Rule Generator .................................................................................276

8.1.3 From Cases to Rule Generation ......................................................279

8.2 Qualitative Control Mechanism...................................................................280

8.2.1 Fuzzy, Probability, and Cloud Control Methods.............................280

8.2.2 Theoretic Explanation of Mamdani Fuzzy Control Method...........289

8.3 Inverted Pendulum — an Example of Intelligent Control

with Uncertainty...........................................................................................291

8.3.1 Inverted Pendulum System and Its Control.....................................291

8.3.2 Inverted Pendulum Qualitative Control Mechanism .......................292

8.3.3 Cloud Control Policy of Triple-Link Inverted Pendulum ...............294

8.3.4 Balancing Patterns of an Inverted Pendulum ..................................302

References..............................................................................................................312

Chapter 9

A New Direction for AI with Uncertainty ......................................315

9.1 Computing with Words ................................................................................316

9.2 Study of Cognitive Physics..........................................................................320

9.2.1 Extension of Cloud Model...............................................................320

9.2.2 Dynamic Data Field .........................................................................323

9.3 Complex Networks with Small World and Scale-Free Models ..................328

9.3.1 Regularity of Uncertainty in Complex Networks ...........................329

9.3.2 Scale-Free Networks Generation .....................................................332

9.3.3 Applications of Data Field Theory to Networked Intelligence ......339

9.4 Long Way to Go for AI with Uncertainty ...................................................340

9.4.1 Limitations of Cognitive Physics Methodology..............................340

9.4.2 Divergences from Daniel, the Nobel Economics Prize Winner......340

References..............................................................................................................342

Research Foundation Support

............................................................................345

Index

 

+ نوشته شده در  دوشنبه سی ام شهریور 1388ساعت 23:37  توسط محسن سیدکاظمی  |