This article treats the problem of vagueness in databases from a general point of view. Several kinds of attribute imprecise values are considered, including the case where such values are fuzzy set of objects. The possibility of managing uncertain data is also taken into account and both sources of
On proof- and model-based techniques for reasoning with uncertainty
✍ Scribed by Flávio S. Corrěa da Silva
- Publisher
- John Wiley and Sons
- Year
- 1995
- Tongue
- English
- Weight
- 578 KB
- Volume
- 10
- Category
- Article
- ISSN
- 0884-8173
No coin nor oath required. For personal study only.
✦ Synopsis
In this article we compare two well-known techniques for reasoning with uncertainty-namely, Incidence Calculus and Fagin-Halpern's version of the Theory of Evidence-from a viewpoint not so frequently explored for such techniques. We argue that, despite the equivalence relations that these techniques have been proved to hold, they have intrinsically different r8les as representations of uncertainty for automated reasoning, in the sense that the former represents approximations to uncertainty values due to impossibility to achieve exact results by proof-theoretic means, and the latter represents model-theoretic limits of definability of uncertainty values.
📜 SIMILAR VOLUMES
Model order reduction of an electromagnetic system is understood as the approximation of a continuous or discrete model of the system by one of substantially lower order, yet capable of capturing the electromagnetic behaviour of the original one with su$cient engineering accuracy. Model order reduct