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Management of Knowledge Imperfection in Building Intelligent Systems

  • Book
  • © 2009

Overview

Authors:
  1. Eugene Roventa

    1. York University, Canada

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    You can also search for this author in PubMed   Google Scholar

  2. Tiberiu Spircu

    1. “Carol Davila” University of Medicine and Pharmacy , Romania

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    You can also search for this author in PubMed   Google Scholar

  • First book treating the knowledge imperfection in building intelligent systems
  • Includes a lot of examples and Visual Prolog programs

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

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Table of contents (10 chapters)

  1. Front Matter

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  2. “Classical” Expert Systems

    • Eugene Roventa, Tiberiu Spircu
    Pages 1-12

  3. Knowledge Representation

    • Eugene Roventa, Tiberiu Spircu
    Pages 13-30

  4. Uncertainty and Classical Theory of Probability

    • Eugene Roventa, Tiberiu Spircu
    Pages 31-87

  5. Statistical Inference

    • Eugene Roventa, Tiberiu Spircu
    Pages 89-131

  6. Bayesian (Belief) Networks

    • Eugene Roventa, Tiberiu Spircu
    Pages 133-152

  7. Certainty Factors Theory

    • Eugene Roventa, Tiberiu Spircu
    Pages 153-160

  8. Belief Theory

    • Eugene Roventa, Tiberiu Spircu
    Pages 161-186

  9. Possibility Theory

    • Eugene Roventa, Tiberiu Spircu
    Pages 187-194

  10. Approximate Reasoning

    • Eugene Roventa, Tiberiu Spircu
    Pages 195-232

  11. Review

    • Eugene Roventa, Tiberiu Spircu
    Pages 233-246

  12. Back Matter

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Keywords

About this book

There are many good AI books. Usually they consecrate at most one or two chapters to the imprecision knowledge processing. To our knowledge this is among the few books to be entirely dedicated to the treatment of knowledge imperfection when bui- ing intelligent systems. We consider that an entire book should be focused on this important aspect of knowledge processing. The expected audience for this book - cludes 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 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. Each chapter ends with a set of carefully pe- gogically chosen exercises, which complete solution provided. Their understanding will trigger the comprehension of the theoretical notions, concepts and results. Chapter 1 is dedicated to the review of expert systems. Hence are briefly discussed production rules, structure of ES, reasoning in an ES, and conflict resolution. Chapter 2 treats knowledge representation. That includes the study of the differences between data, information and knowledge, logical systems with focus on predicate calculus, inference rules in classical logic, semantic nets and frames.

Authors and Affiliations

  • York University, Canada

    Eugene Roventa

  • “Carol Davila” University of Medicine and Pharmacy , Romania

    Tiberiu Spircu

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