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Elicitation, assessment and pooling of expert judgements using possibility theory. (English) Zbl 0884.68118
Vogt, Carlos, First COMPAQ Prize for stimulation of research and development in computer science. São Paulo: Instituto Uniemp, 49-85 (1996).
Summary: The problem of modelling expert knowledge about numerical parameters in the field of reliability is considered in the framework of possibility theory. Usually expert opinions about quantities such as failure rates are modelled, assessed and pooled in the setting of probability theory. This approach does not seem to always be natural since probabilistic information looks too rich to be currently supplied by individuals. Indeed, information supplied by individuals is often incomplete, imprecise rather than tainted with randomness. Moreover, the probabilistic framework looks somewhat restrictive to express the variety of possible pooling modes. In this paper, we formulate a model of expert opinion by means of possibility distributions that are thought to better reflect the imprecision pervading expert judgements. They are weak substitutes to unreachable subjective probabilities. Assessment evaluation is carried out in terms of calibration and level of precision, respectively measured by membership grades and fuzzy cardinality indices. Lastly, drawing from previous works on data fusion using possibility theory, we present various pooling modes with their formal model under various assumptions concerning the experts. A comparative experiment between two computerized systems for expert opinion analysis has been carried out, and its results are presented in this paper.
For the entire collection see [Zbl 0874.00029].

MSC:
68T27 Logic in artificial intelligence
68T35 Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence
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