Advertisement

Management of Knowledge Imperfection in Building Intelligent Systems

  • Eugene Roventa
  • Tiberiu Spircu

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 227)

Table of contents

  1. Front Matter
  2. Eugene Roventa, Tiberiu Spircu
    Pages 1-12
  3. Eugene Roventa, Tiberiu Spircu
    Pages 13-30
  4. Eugene Roventa, Tiberiu Spircu
    Pages 31-87
  5. Eugene Roventa, Tiberiu Spircu
    Pages 89-131
  6. Eugene Roventa, Tiberiu Spircu
    Pages 133-152
  7. Eugene Roventa, Tiberiu Spircu
    Pages 153-160
  8. Eugene Roventa, Tiberiu Spircu
    Pages 161-186
  9. Eugene Roventa, Tiberiu Spircu
    Pages 187-194
  10. Eugene Roventa, Tiberiu Spircu
    Pages 195-232
  11. Eugene Roventa, Tiberiu Spircu
    Pages 233-246
  12. Back Matter

About this book

Introduction

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.

Keywords

Approximate Reasoning Building Intelligent Systems Bézier Curves Knowledge Imperfection STATISTICA Uncertain Reasoning artificial intelligence expert system knowledge knowledge representation

Authors and affiliations

  • Eugene Roventa
    • 1
  • Tiberiu Spircu
    • 2
  1. 1.York UniversityCanada
  2. 2.“Carol Davila” University of Medicine and Pharmacy Romania

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-77463-1
  • Copyright Information Springer Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-77462-4
  • Online ISBN 978-3-540-77463-1
  • Series Print ISSN 1434-9922
  • Series Online ISSN 1860-0808
  • Buy this book on publisher's site