On cautious probabilistic inference and default detachment View Full Text


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Article Info

DATE

1995-02

AUTHORS

Helmut Thöne, Werner Kießling, Ulrich Güntzer

ABSTRACT

Conditional probabilities are one promising and widely used approach to model uncertainty in information systems. This paper discusses the DUCK-calculus, which is founded on the cautious approach to uncertain probabilistic inference. Based on a set of sound inference rules, derived probabilistic information is gained by local bounds propagation techniques. Precision being always a central point of criticism to such systems, we demonstrate that DUCK need not necessarily suffer from these problems. We can show that the popular Bayesian networks are subsumed by DUCK, implying that precise probabilities can be deduced by local propagation techniques, even in the multiply connected case. A comparative study with INFERNO and with inference techniques based on global operations-research techniques yields quite favorable results for our approach. Since conditional probabilities are also suited to model nonmonotonic situations by considering different contexts, we investigate the problems of maximal and relevant contexts, needed to draw default conclusions about individuals. More... »

PAGES

195-224

References to SciGraph publications

  • 1992. Database support for problematic knowledge in ADVANCES IN DATABASE TECHNOLOGY — EDBT '92
  • 1991. Uncertainty and Vagueness in Knowledge Based Systems, Numerical Methods in NONE
  • 1993. Fixpoint Evaluation with Subsumption for Probabilistic Uncertainty in DATENBANKSYSTEME IN BÜRO, TECHNIK UND WISSENSCHAFT
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    http://scigraph.springernature.com/pub.10.1007/bf02031721

    DOI

    http://dx.doi.org/10.1007/bf02031721

    DIMENSIONS

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