Quantified Representation of Uncertainty and Imprecision

  • Philippe Smets

Table of contents

  1. Front Matter
    Pages i-viii
  2. Giovanni Panti
    Pages 25-74
  3. Vilém Novák
    Pages 75-109
  4. Colin Howson
    Pages 111-134
  5. Donald Gillies
    Pages 135-167
  6. Didier Dubois, Henri Prade
    Pages 169-226
  7. Henry E. Kyburg Jr.
    Pages 227-245
  8. Nils-Eric Sahlin, Wlodek Rabinowicz
    Pages 247-265
  9. Anthony W. F. Edwards
    Pages 357-366
  10. Brian Skyrms, Peter Vanderschraaf
    Pages 391-439
  11. Gerd Gigerenzer
    Pages 441-467
  12. Back Matter
    Pages 469-477

About this book


We are happy to present the first volume of the Handbook of Defeasible Reasoning and Uncertainty Management Systems. Uncertainty pervades the real world and must therefore be addressed by every system that attempts to represent reality. The representation of uncertainty is a ma­ jor concern of philosophers, logicians, artificial intelligence researchers and com­ puter sciencists, psychologists, statisticians, economists and engineers. The present Handbook volumes provide frontline coverage of this area. This Handbook was produced in the style of previous handbook series like the Handbook of Philosoph­ ical Logic, the Handbook of Logic in Computer Science, the Handbook of Logic in Artificial Intelligence and Logic Programming, and can be seen as a companion to them in covering the wide applications of logic and reasoning. We hope it will answer the needs for adequate representations of uncertainty. This Handbook series grew out of the ESPRIT Basic Research Project DRUMS II, where the acronym is made out of the Handbook series title. This project was financially supported by the European Union and regroups 20 major European research teams working in the general domain of uncertainty. As a fringe benefit of the DRUMS project, the research community was able to create this Hand­ book series, relying on the DRUMS participants as the core of the authors for the Handbook together with external international experts.


fuzzy fuzzy logic statistical inference uncertainty

Editors and affiliations

  • Philippe Smets
    • 1
  1. 1.IRIDIAUniversité Libre de BruxellesBelgium

Bibliographic information

  • DOI
  • Copyright Information Springer Science+Business Media Dordrecht 1998
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-90-481-5038-0
  • Online ISBN 978-94-017-1735-9
  • Buy this book on publisher's site