Ebook: Management of Knowledge Imperfection in Building Intelligent Systems
- Tags: Appl.Mathematics/Computational Methods of Engineering, Artificial Intelligence (incl. Robotics), Computer Imaging Vision Pattern Recognition and Graphics, Computer-Aided Engineering (CAD CAE) and Design, Applications of Mathematics, O
- Series: Studies in Fuzziness and Soft Computing 227
- Year: 2009
- Publisher: Springer-Verlag Berlin Heidelberg
- Edition: 1
- Language: English
- pdf
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, IT&C, mathematics, business, medicine, etc., graduates, specialists and researchers in these fields. The subjects treated in the book include expert systems, knowledge representa-tion, 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. Each chapter ends with a set of carefully pedagogically chosen exercises, which complete solution provided. Their understanding will trigger the comprehension of the theoretical notions, concepts and results.
Features of the book:
a) Comprehensive comparative approach to deal with most of the techniques of management of knowledge imperfection
b) Breakthrough fuzzy techniques approach for handling real word imprecision
c) Numerous examples throughout the book in the medical domain
d) Each chapter is followed by a set of detailed solved exercises.
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, IT&C, mathematics, business, medicine, etc., graduates, specialists and researchers in these fields. The subjects treated in the book include expert systems, knowledge representa-tion, 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. Each chapter ends with a set of carefully pedagogically chosen exercises, which complete solution provided. Their understanding will trigger the comprehension of the theoretical notions, concepts and results.
Features of the book:
a) Comprehensive comparative approach to deal with most of the techniques of management of knowledge imperfection
b) Breakthrough fuzzy techniques approach for handling real word imprecision
c) Numerous examples throughout the book in the medical domain
d) Each chapter is followed by a set of detailed solved exercises.
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, IT&C, mathematics, business, medicine, etc., graduates, specialists and researchers in these fields. The subjects treated in the book include expert systems, knowledge representa-tion, 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. Each chapter ends with a set of carefully pedagogically chosen exercises, which complete solution provided. Their understanding will trigger the comprehension of the theoretical notions, concepts and results.
Features of the book:
a) Comprehensive comparative approach to deal with most of the techniques of management of knowledge imperfection
b) Breakthrough fuzzy techniques approach for handling real word imprecision
c) Numerous examples throughout the book in the medical domain
d) Each chapter is followed by a set of detailed solved exercises.
Content:
Front Matter....Pages -
“Classical” Expert Systems....Pages 1-12
Knowledge Representation....Pages 13-30
Uncertainty and Classical Theory of Probability....Pages 31-87
Statistical Inference....Pages 89-131
Bayesian (Belief) Networks....Pages 133-152
Certainty Factors Theory....Pages 153-160
Belief Theory....Pages 161-186
Possibility Theory....Pages 187-194
Approximate Reasoning....Pages 195-232
Review....Pages 233-246
Back Matter....Pages -
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, IT&C, mathematics, business, medicine, etc., graduates, specialists and researchers in these fields. The subjects treated in the book include expert systems, knowledge representa-tion, 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. Each chapter ends with a set of carefully pedagogically chosen exercises, which complete solution provided. Their understanding will trigger the comprehension of the theoretical notions, concepts and results.
Features of the book:
a) Comprehensive comparative approach to deal with most of the techniques of management of knowledge imperfection
b) Breakthrough fuzzy techniques approach for handling real word imprecision
c) Numerous examples throughout the book in the medical domain
d) Each chapter is followed by a set of detailed solved exercises.
Content:
Front Matter....Pages -
“Classical” Expert Systems....Pages 1-12
Knowledge Representation....Pages 13-30
Uncertainty and Classical Theory of Probability....Pages 31-87
Statistical Inference....Pages 89-131
Bayesian (Belief) Networks....Pages 133-152
Certainty Factors Theory....Pages 153-160
Belief Theory....Pages 161-186
Possibility Theory....Pages 187-194
Approximate Reasoning....Pages 195-232
Review....Pages 233-246
Back Matter....Pages -
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