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Algorithms for precise and imprecise conditional probability assessments. (English) Zbl 0859.68042

Coletti, Giulianella (ed.) et al., Mathematical models for handling partial knowledge in artificial intelligence. Selected papers from a workshop, Sicily, Italy, June 19-25, 1994. New York, NY: Plenum Press. 231-254 (1995).
Summary: We consider some applications of our procedure to check coherence of precise and imprecise conditional probability assessments. In the next Section, after reviewing some preliminary concepts and results, we describe the algorithm checking coherence. In the subsequent Section we apply the algorithm to the case of precise probabilities and we give an example of a function \(p\), defined on a class of conditional events, which satisfies the laws of a conditional probability but is not coherent. In the last Section we analyze the case of imprecise probabilities considering two inference rules (the disjunction and triangularity rules) well known in plausible reasoning. We examine the propagation of some probability lower bounds obtaining exact formulas and improving the results given by other authors.
For the entire collection see [Zbl 0845.00054].

MSC:

68W10 Parallel algorithms in computer science
68T35 Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence
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