Special Issue from Workshop on Uncertainty Frameworks in Nonmonotonic ReasoningScope of the Workshop on Uncertainty Frameworks in NMR
Many approaches have been developed for reasoning under incomplete information with uncertain rules having exceptions. Some of them are symbolic and based on a logical framework or on logic programming; others are more numerically oriented and make use of probabilities, belief and plausibility functions, or qualitative or quantitative possibilities. The Uncertainty and NMR session is organized in five sections which cover a good sampling of issues at the interface between nonmonotonic reasoning and uncertainty modelling. The first section deals with probabilistic approaches to NMR ranging from bayesian networks to qualitative probabilities, and to reasoning with interval-valued conditionals. The second section discusses System P (proposed by Kraus, Lehmann and Magidor) from probabilistic and empirical cognitive points of view respectively. The third section is about similarity relations in NMR, while the papers of the fourth section are argumentation-oriented. Two papers in these two sections refer to belief and plausibility functions. The last section deals with information fusion and multi-agent in frameworks where information can be prioritized.Latest update: 12.3.2000; Position code: C.etai.ufn.scope.