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Plausible reasoning and graded information: A unified approach

机译:合理的推理和分级信息:统一方法

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摘要

We propose a formal method for reasoning both under uncertainty and under vagueness in a coherent way. We deal with implicational relationships where an explicit numerical degree is used to express uncertainty. The approach relies on Dubois and Prade's Possibilistic Logic. Furthermore, we take the possible vagueness of the involved properties into account. Namely, we deal with properties of the form that some vague criterion is fulfilled to a specific degree. Thus vague properties are treated as parametrised sets of crisp properties. Finally, a rule is included to ensure smoothness of the uncertainty degree with regard to changes of the degrees to which the properties under consideration hold. The calculus is applicable wherever graded properties are subject to uncertainty. Vagueness and uncertainty are treated independently, but can optionally be interconnected in a controlled way. A specific application suggests itself in the field of medical expert systems.
机译:我们提出了一种形式化的方法,以连贯的方式在不确定性和模糊性下进行推理。我们处理隐含关系,其中使用显式数值度表示不确定性。该方法依赖于Dubois和Prade的可能性逻辑。此外,我们考虑了所涉及属性的可能模糊性。即,我们处理某种程度的模糊标准在特定程度上得到满足的形式的性质。因此,模糊属性被视为脆性的参数化组。最后,包括一个规则,以确保不确定度的平滑度与所考虑的属性的保持度有关。该演算适用于分级属性易受不确定性影响的任何地方。模糊性和不确定性是独立处理的,但可以选择以受控方式互连。在医学专家系统领域中,一种特定的应用提出了自己。

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