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Uncertain Information

  • Jürg Kohlas
Part of the Discrete Mathematics and Theoretical Computer Science book series (DISCMATH)

Abstract

Information can be uncertain. Uncertainty may arise because events depend on random elements or uncertainty may be due to incomplete knowledge. In any case, information can often be asserted only with a certain probability. In this chapter we show that information algebras provide a natural framework to describe uncertainty. We start by modeling uncertainty in information algebras by (generalized) random variables, taking values in information algebras. This extends the fundamental work of A. Dempster (Dempster, 1967) and G. Shafer (Shafer, 1976) to the framework of information algebras. In the following Section 7.2 we show, how generalized random variables arise in a natural way from assumption-based reasoning in information systems. This is an extension of the idea of “probaility of provability” introduced by Pearl (Pearl, 1988) and also discussed by (Laskey & Lehner, 1989). This idea has evolved into so-called probabilistic argumentation systems (Haenni, Kohlas & Lehmann, 2000). Closely related to such systems are structures called hints. The notion of a hint has been introduced in (Kohlas & Monney, 1995).

Keywords

Support Function Simple Experiment Focal Element Basic Probability Assignment Argumentation System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London 2003

Authors and Affiliations

  • Jürg Kohlas
    • 1
  1. 1.Department of InformaticsUniversity of FribourgFribourgSwitzerland

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