Management of Knowledge Imperfection in Building Intelligent Systems

by Roventa, Eugene; Spircu, Tiberiu

• ISBN13: 9783540774624
• ISBN10: 3540774629
• eBook ISBN(s): 9783540774631
• Format: Hardcover
• Copyright: 2008-12-04
• Publisher: Springer-Verlag New York Inc
• More Book Details
• Purchase Benefits

Summary

"There are many good AI books. Usually they consecrate at most one or two chapters to the imprecision knowledge processing. This book is among the few books to be entirely dedicated to the treatment of knowledge imperfection when building intelligent systems. We consider that an entire book should be focused on this important aspect of knowledge processing. The expected audience for this book includes undergraduate students in computer science, ITC, mathematics, business, medicine, etc., graduates, specialists and researchers in these fields. The subjects treated in the book include expert systems, knowledge representation, reasoning under knowledge Imperfection (Probability Theory, Possibility Theory, Belief Theory, and Approximate Reasoning). Most of the examples discussed in details throughout the book are from the medical domain."--BOOK JACKET.

Table of Contents

Preface	p. V
Notations	p. VII
"Classical" Expert Systems	p. 1
Production Rules	p. 1
Expert Systems	p. 3
Structure of Rule-Based Expert Systems	p. 4
Reasoning in an Expert System	p. 5
Conflicts Resolution	p. 9
Solved Exercises	p. 10
Knowledge Representation	p. 13
Data, Information and Knowledge	p. 13
Logical Systems	p. 14
Predicate Calculus	p. 19
Inference Rules in Classical Logic	p. 22
Semantic Nets	p. 23
Frames	p. 24
Solved Exercises	p. 27
Uncertainty and Classical Theory of Probability	p. 31
Taxonomy of Imperfection	p. 31
Usual and Precise Meaning	p. 33
Experiments and Events	p. 35
Formal Definition of Events	p. 39
Defining Probabilities	p. 41
Defining Probabilities (II)	p. 44
Bayes' Theorem	p. 47
Misleading Aspects	p. 49
Random Variables and Distributions	p. 50
Expectation and Variance	p. 51
Examples of Discrete Distributions	p. 56
Continuous Distributions	p. 60
Examples of Continuous Distributions. Normal	p. 64
Examples of Continuous Distributions. Chi-square	p. 67
Student and Fisher-Snedecor Distributions	p. 70
Formal definition of Random Variables	p. 73
Probabilities of Formulas	p. 76
Solved Exercises	p. 82
Statistical Inference	p. 89
Inferring Scientific Truth: Tests of Significance	p. 89
Relation "Alternative Hypothesis - Null Hypothesis"	p. 91
Hypothesis Testing, the Classical Approach	p. 93
Examples: Comparing Means	p. 94
Comparing Means, the Practical Approach	p. 104
Paired and Unpaired Tests	p. 105
Example: Comparing Proportions	p. 107
Goodness-of-Fit: Chi-square	p. 112
Other Goodness-of-Fit Tests	p. 119
Nonparametric Tests. Wilcoxon/Mann-Whitney	p. 120
Analysis of Variance	p. 124
Summary	p. 126
Solved Exercises	p. 127
Bayesian (Belief) Networks	p. 133
Uncertain Production Rules	p. 133
Bayesian (Belief, Causal) Networks	p. 135
Examples of Bayesian Networks	p. 138
Software	p. 144
Bias of the Bayesian (Probabilistic) Method	p. 148
Solved Exercises	p. 148
Certainty Factors Theory	p. 153
Certainty Factors	p. 153
Stanford Algebra	p. 154
Certainty Factors and Measures of Belief and Disbelief	p. 156
Solved Exercises	p. 158
Belief Theory	p. 161
Belief Approach	p. 161
Agreement Measures	p. 163
Dempster-Shafer Theory	p. 165
The Pignistic Transform	p. 171
Combining Beliefs. The Dempster's Formula	p. 172
Difficulties with Dempster-Shafer's Theory	p. 176
Specializations and the Transferable Belief Model	p. 177
Conditional Beliefs and the Generalized Bayesian Theorem	p. 180
Solved Exercises	p. 181
Possibility Theory	p. 187
Necessity and Possibility Measures	p. 187
Conditional Possibilities	p. 190
Exercises	p. 193
Approximate Reasoning	p. 195
Fuzzy Sets, Fuzzy Numbers, Fuzzy Relations	p. 195
Fuzzy Propositions and Fuzzy Logic	p. 204
Hedges	p. 206
Fuzzy Logic	p. 212
Approximate Reasoning	p. 218
Defuzzification	p. 224
Approach by Precision Degrees	p. 226
Solved Exercises	p. 228
Review	p. 233
Review of Uncertainty and Imprecision	p. 233
Production Rules	p. 239
Perception-Based Theory	p. 242
Solved Exercises	p. 244
References	p. 247
Index	p. 251
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