Possibility Theory An Approach to Computerized Processing of Uncertainty

Possibility Theory An Approach to Computerized Processing of Uncertainty / by Didier Dubois, Henri Prade.

In the evolution of scientific theories, concern with uncertainty is almost invariably a concomitant of maturation. This is certainly true of the evolution· of physics, economics, operations research, communication sciences, and a host of other fields. And it is true of what has been happening more...

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Bibliographic Details
Main Authors: Dubois, Didier (Author), Prade, Henri (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: New York, NY : Springer US : Imprint: Springer, 1988.
Edition:1st ed. 1988.
Series:Springer eBook Collection.
Subjects:
Statistics .
Computer science.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • 1. Measures of Possibility and Fuzzy Sets
  • 1.1. Imprecision and Uncertainty
  • 1.2. Traditional Models of Imprecision and Uncertainty
  • 1.3. Confidence Measures
  • 1.4. Fuzzy Sets
  • 1.5. Elementary Fuzzy Set Operations
  • 1.6. Practical Methods for Determining Membership Functions
  • 1.7. Confidence Measures for a Fuzzy Event
  • 1.8. Fuzzy Relations and Cartesian Products of Fuzzy Sets
  • References
  • 2. The Calculus of Fuzzy Quantities
  • 2.1. Definitions and a Fundamental Principle
  • 2.2. Calculus of Fuzzy Quantities with Noninteractive Variables
  • 2.3. Practical Calculation with Fuzzy Intervals
  • 2.4. Further Calculi of Fuzzy Quantities
  • 2.5. Illustrative Examples
  • Appendix: Computer Programs
  • References
  • 3. The Use of Fuzzy Sets for the Evaluation and Ranking of Objects
  • 3.1. A Quantitative Approach to Multiaspect Choice
  • 3.2. Comparison of Imprecise Evaluations
  • Appendix: Computer Programs
  • References
  • 4. Models for Approximate Reasoning in Expert Systems
  • 4.1. Remarks on Modeling Imprecision and Uncertainty
  • 4.2. Reasoning from Uncertain Premises
  • 4.3. Inference from Vague or Fuzzy Premises
  • 4.4. Brief Summary of Current Work and Systems
  • 4.5. Example
  • Appendix A.
  • Appendix B: Computer Programs
  • References
  • 5. Heuristic Search in an Imprecise Environment, and Fuzzy Programming
  • 5.1. Heuristic Search in an Imprecise Environment
  • 5.2. An Example of Fuzzy Programming: Tracing the Execution of an Itinerary Specified in Imprecise Terms
  • Appendix: Computer Programs
  • A.1. Selection of “the Smallest” of N Fuzzy Numbers
  • A.2. Tracing Imprecisely Specified Itineraries
  • References
  • 6. Handling of Incomplete or Uncertain Data and Vague Queries in Database Applications
  • 6.1. Representation of Incomplete or Uncertain Data
  • 6.2. The Extended Relational Algebra and the Corresponding Query Language
  • 6.3. Example
  • 6.4. Conclusion
  • Appendix: Computer Program
  • A.1. Data Structures
  • A.2. Representation of Queries
  • A.3. Description of Implemeted Procedures
  • References.

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