Symbolic and Quantitative Approaches to Reasoning and Uncertainty

1. Front Matter

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2. \(\mathcal{R}\mathcal{E}\mathcal{S}\): A formalism for reasoning with relative-strength defaults

   • Z. An, M. McLeish

   Pages 1-8

3. A semantics for open normal defaults via a modified preferential approach

   • Franz Baader, Karl Schlechta

   Pages 9-16

4. Possibilistic logic: From nonmonotonicity to logic programming

   • Salem Benferhat, Didier Dubois, Henri Prade

   Pages 17-24

5. Learning membership functions

   • Francesco Bergadano, Vincenzo Cutello

   Pages 25-32

6. The use of possibilistic logic PL1 in a customizable tool for the generation of production-rule based systems

   • Guilherme Bittencourt, Maurício Marengoni, Sandra Sandri

   Pages 33-40

7. Probabilistic network construction using the minimum description length principle

   • Remco R. Bouckaert

   Pages 41-48

8. IDAGs: A perfect map for any distribution

   • Remco R. Bouckaert

   Pages 49-56

9. Learning non probabilistic belief networks

   • Luis M. de Campos, Juan F. Huete

   Pages 57-64

10. A practical system for defeasible reasoning and belief revision

    • Maria R. Cravo, João P. Martins

    Pages 65-72

11. Influence of granularity level in fuzzy functional dependencies

    • J. C. Cubero, J. M. Medina, M. A. Vila

    Pages 73-78

12. A logic for reasoning about safety in decision support systems

    • S. K. Das, J. Fox

    Pages 79-84

13. Acceptability of arguments as ‘logical uncertainty’

    • Morten Elvang-Gøransson, Paul J. Krause, John Fox

    Pages 85-90

14. A temporal model theory for default logic

    • Joeri Engelfriet, Jan Treur

    Pages 91-96

15. Uncertainty in constraint satisfaction problems: A probabilistic approach

    • Hélène Fargier, Jérôme Lang

    Pages 97-104

16. Interference logic = conditional logic + frame axiom

    • L. Fariñas del Cerro, A. Herzig

    Pages 105-112

17. A unifying logical framework for reason maintenance

    • Detlef Fehrer

    Pages 113-120

18. Taxonomic linear theories

    • Christophe Fouqueré, Jacqueline Vauzeilles

    Pages 121-128

19. Making inconsistency respectable: Part 2 — Meta-level handling of inconsistency

    • Dov Gabbay, Anthony Hunter

    Pages 129-136

20. Restricted access logics for inconsistent information

    • Dov Gabbay, Anthony Hunter

    Pages 137-144

In recent years it has become apparent that an important part of the theory of artificial intelligence is concerned with reasoning on the basis of uncertain, incomplete, or inconsistent information. A variety of formalisms have been developed, including nonmonotonic logic, fuzzy sets, possibility theory, belief functions, and dynamic models of reasoning such as belief revision and Bayesian networks. Several European research projects have been formed in the area and the first European conference was held in 1991. This volume contains the papers accepted for presentation at ECSQARU-93, the European Conference on Symbolicand Quantitative Approaches to Reasoning and Uncertainty, held at the University of Granada, Spain, November 8-10, 1993.

• Bayesian network
• Dynamic Reasoning
• Dynamisches Schließen
• Fuzzy Mengen
• Fuzzy Sets
• Möglichkeitstheorie
• Nichtmonotone Logik
• Possibility Theory
• artificial intelligence
• constraint satisfaction problem
• expert system
• intelligence
• knowledge base
• learning
• probabilistic network

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