Communication Dans Un Congrès Année : 2024

Elicitation for Decision Problems Under Severe Uncertainties

Résumé

In this paper, we investigate the problem of eliciting information from an expert, where the assumed uncertainty model is a coherent upper prevision (or equivalently a closed convex set of probabilities). The goal is to solve a decision problem under the maximality decision rule, with as few queries to the expert as possible. To address this, we study the range of coherent upper bounds an expert may give on a given query. In doing so, we provide new results and characterisations for this range. We then use these results to provide an algorithm of elicitation. We illustrate the algorithm on an example.
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hal-04917968 , version 1 (28-01-2025)

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Nawapon Nakharutai, Matthias Troffaes, Sébastien Destercke. Elicitation for Decision Problems Under Severe Uncertainties. Scalable Uncertainty Management (SUM 2024), Oct 2024, Palermo (Italy), Italy. pp.312-324, ⟨10.1007/978-3-031-76235-2_23⟩. ⟨hal-04917968⟩
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