Quantified Representation of Uncertainty and Imprecision

1. Front Matter

   Pages i-viii

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2. Probability, Possibility, Belief: Which and Where?

   • Philippe Smets

   Pages 1-24

3. Multi-Valued Logics

   • Giovanni Panti

   Pages 25-74

4. Fuzzy Logic

   • Vilém Novák

   Pages 75-109

5. The Bayesian Approach

   • Colin Howson

   Pages 111-134

6. Confirmation Theory

   • Donald Gillies

   Pages 135-167

7. Possibility Theory: Qualitative and Quantitative Aspects

   • Didier Dubois, Henri Prade

   Pages 169-226

8. Families of Probabilities

   • Henry E. Kyburg Jr.

   Pages 227-245

9. The Evidentiary Value Model

   • Nils-Eric Sahlin, Wlodek Rabinowicz

   Pages 247-265

10. The Transferable Belief Model for Quantified Belief Representation

    • Philippe Smets

    Pages 267-301

11. Infinitesimal Theories of Uncertainty for Plausible Reasoning

    • Salem Benferhat

    Pages 303-356

12. Statistical Inference

    • Anthony W. F. Edwards

    Pages 357-366

13. Graphical Models for Probabilistic and Causal Reasoning

    • Judea Pearl

    Pages 367-389

14. Game Theory

    • Brian Skyrms, Peter Vanderschraaf

    Pages 391-439

15. Psychological Challenges for Normative Models

    • Gerd Gigerenzer

    Pages 441-467

16. Back Matter

    Pages 469-477

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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

• IRIDIA, Université Libre de Bruxelles, Belgium

  Philippe Smets

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