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Ignorance and the Expressiveness of Single- and Set-Valued Probability Models of Belief

机译:信念的单值和集值概率模型的无知与表示

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Over time, there have been refinements in the way that probability distributions are used for representing beliefs. Models which rely on single probability distributions depict a complete ordering among the propositions of interest, yet human beliefs are sometimes not completely ordered. Non-singleton sets of probability distributions can represent partially ordered beliefs. Convex sets are particularly convenient and expressive, but it is known that there are reasonable patterns of belief whose faithful representation require less restrictive sets. The present paper shows that prior ignorance about three or more exclusive alternatives and the emergence of partially ordered beliefs when evidence is obtained defy representation by any single set of distributions, but yield to a representation based on several sets. The partial order is shown to be a partial qualitative probability which shares some intuitively appealing attributes with probability distributions.
机译:随着时间的流逝,使用概率分布表示信念的方式有了一些改进。依赖单一概率分布的模型描述了所关注的命题之间的完整排序,但是人类的信念有时并未完全排序。概率分布的非单子集可以表示部分有序的信念。凸集特别方便和富有表现力,但众所周知,有合理的信念模式,其忠实的表现形式需要较少的约束集。本文表明,对于三个或更多排他性选择的先验无知,以及当获得证据时出现部分有序信念的情况,都无法通过任何单一的分布集来表示,但是会屈服于基于多个集合的表示。偏序显示为部分定性概率,具有概率分布具有一些直观上吸引人的属性。

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