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Imprecise Swing Weighting for Multi-Attribute Utility Elicitation Based on Partial Preferences

Conference Paper Artificial Intelligence · Imprecise Probability · Uncertainty in Artificial Intelligence

Abstract

We describe a novel approach to multi-attribute utility elicitation which is both general enough to cover a wide range of problems, whilst at the same time simple enough to admit reasonably straightforward calculations. We allow both utilities and probabilities to be only partially specified, through bounding. We still assume marginal utilities to be precise. We derive necessary and sufficient conditions under which our elicitation procedure is consistent. As a special case, we obtain an imprecise generalization of the well known swing weighting method for eliciting multi-attribute utility functions. An example from ecological risk assessment demonstrates our method.

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Context

Venue
International Symposium on Imprecise Probabilities: Theories and Applications
Archive span
2017-2025
Indexed papers
59
Paper id
111174092455561544
v2026.09.13