© 1995

Proceedings of the ISSEK94 Workshop on Mathematical and Statistical Methods in Artificial Intelligence

  • G. Della Riccia
  • R. Kruse
  • R. Viertl
Conference proceedings

Part of the International Centre for Mechanical Sciences book series (CISM, volume 363)

Table of contents

  1. Front Matter
    Pages ii-viii
  2. J. Gebhardt, R. Kruse
    Pages 23-32
  3. R. Viertl
    Pages 33-49
  4. U. G. Oppel, A. Hierle, M. Noormohammadian
    Pages 59-87
  5. F. Bergadano, Ph. Besnard
    Pages 105-118
  6. D. Gunetti
    Pages 131-146
  7. P. Hájek
    Pages 147-155
  8. U. Pompe, I. Kononenko
    Pages 185-198
  9. I. Kononenko, E. Simec
    Pages 199-220
  10. M. Bohanec, I. Bratko
    Pages 221-235
  11. F. Suggi Liverani
    Pages 237-245
  12. B. A. Teather, G. Della Riccia, D. Teather
    Pages 247-256

About these proceedings


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. Classical logic and probability theory are only partially adequate for this, and a variety of other formalisms have been developed, some of the most important being fuzzy methods, possibility theory, belief function theory, non monotonic logics and modal logics. The aim of this workshop was to contribute to the elucidation of similarities and differences between the formalisms mentioned above.


artificial intelligence fuzzy methods intelligence probability probability theory statistical methods

Editors and affiliations

  • G. Della Riccia
    • 1
  • R. Kruse
    • 2
  • R. Viertl
    • 3
  1. 1.University of UdineItaly
  2. 2.University of BraunschweigGermany
  3. 3.Technical University of WienAustria

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