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

机译:基于部分首选项的多属性效用启发的不精确摆动加权

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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.
机译:我们描述了一种新颖的多属性效用启发方法,该方法既通用又足以涵盖广泛的问题,同时又足够简单,可以接受合理直接的计算。通过边界,我们只允许部分指定实用程序和概率。我们仍然假设边际效用是精确的。我们得出诱导程序一致的必要条件和充分条件。作为一种特殊情况,我们得出了众所周知的挥杆加权方法的不精确概括,该方法用于引发多属性效用函数。生态风险评估中的一个例子证明了我们的方法。

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