Artificial Intelligence : A Guide to Intelligent Systems (1ST)

Artificial Intelligence : A Guide to Intelligent Systems (1ST)

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  • 製本 Hardcover:ハードカバー版/ページ数 394 p.
  • 言語 ENG
  • 商品コード 9780201711592
  • DDC分類 006.3

Table of Contents

Preface                                            xi
Acknowledgements xv
Introduction to knowledge-based intelligent 1 (24)
systems
Intelligent machines, or what machines can 1 (3)
do
The history of artificial intelligence, or 4 (13)
from the 'Dark Ages' to knowledge-based
systems
Summary 17 (8)
Questions for review 21 (1)
References 22 (3)
Rule-based expert systems 25 (30)
Introduction, or what is knowledge? 25 (1)
Rules as a knowledge representation 26 (2)
technique
The main players in the expert system 28 (2)
development team
Structure of a rule-based expert system 30 (3)
Fundamental characteristics of an expert 33 (2)
system
Forward chaining and backward chaining 35 (6)
inference techniques
Thermostat: a demonstration rule-based 41 (5)
expert system
Conflict resolution 46 (3)
Advantages and disadvantages of rule-based 49 (2)
expert systems
Summary 51 (4)
Questions for review 53 (1)
References 53 (2)
Uncertainty management in rule-based expert 55 (32)
systems
Introduction, or what is uncertainty? 55 (2)
Basic probability theory 57 (4)
Bayesian reasoning 61 (4)
Forecast: Bayesian accumulation of evidence 65 (7)
Bias of the Bayesian method 72 (2)
Certainty factors theory and evidential 74 (6)
reasoning
Forecast: an application of certainty 80 (2)
factors
Comparison of Bayesian reasoning and 82 (1)
certainty factors
Summary 83 (4)
Questions for review 85 (1)
References 85 (2)
Fuzzy expert systems 87 (42)
Introduction, or what is fuzzy thinking? 87 (2)
Fuzzy sets 89 (5)
Linguistic variables and hedges 94 (3)
Operations of fuzzy sets 97 (6)
Fuzzy rules 103(3)
Fuzzy inference 106(8)
Building a fuzzy expert system 114(11)
Summary 125(4)
Questions for review 126(1)
References 127(1)
Bibliography 127(2)
Frame-based expert systems 129(34)
Introduction, or what is a frame? 129(2)
Frames as a knowledge representation 131(5)
technique
Inheritance in frame-based systems 136(4)
Methods and demons 140(4)
Interaction of frames and rules 144(3)
Buy Smart: a frame-based expert system 147(12)
Summary 159(4)
Questions for review 161(1)
References 161(1)
Bibliography 162(1)
Artificial neural networks 163(54)
Introduction, or how the brain works 163(3)
The neuron as a simple computing element 166(2)
The perceptron 168(5)
Multilayer neural networks 173(10)
Accelerated learning in multilayer neural 183(3)
networks
The Hopfield network 186(8)
Bidirectional associative memory 194(4)
Self-organising neural networks 198(12)
Summary 210(7)
Questions for review 213(1)
References 214(3)
Evolutionary computation 217(40)
Introduction, or can evolution be 217(1)
intelligent?
Simulation of natural evolution 217(3)
Genetic algorithms 220(10)
Why genetic algorithms work 230(3)
Case study: maintenance scheduling with 233(7)
genetic algorithms
Evolution strategies 240(3)
Genetic programming 243(9)
Summary 252(5)
Questions for review 253(1)
References 254(3)
Hybrid Intelligent systems 257(42)
Introduction, or how to combine German 257(2)
mechanics with Italian love
Neural expert systems 259(7)
Neuro-fuzzy systems 266(9)
ANFIS: Adaptive Neuro-Fuzzy Inference System 275(8)
Evolutionary neural networks 283(5)
Fuzzy evolutionary systems 288(6)
Summary 294(5)
Questions for review 295(1)
References 296(3)
Knowledge engineering and data mining 299(46)
Introduction, or what is knowledge 299(7)
engineering?
Will an expert system work for my problem? 306(9)
Will a fuzzy expert system work for my 315(6)
problem?
Will a neural network work for my problem? 321(9)
Data mining and knowledge discovery 330(11)
Summary 341(4)
Questions for review 342(1)
References 343(2)
Glossary 345(26)
Appendix 371(16)
Index 387