To help computers make better decisions, it is desirable to describe all our knowledge in computer-understandable terms. This is easy for knowledge described in terms on numerical values: we simply store the corresponding numbers in the computer. This is also easy for knowledge about precise (well-defined) properties which are either true or false for each object: we simply store the corresponding “true” and “false” values in the computer. The challenge is how to store information about imprecise properties. In this paper, we overview different ways to fully store the expert information about imprecise properties. We show that in the simplest case, when the only source of imprecision is disagreement between different experts, a natural way to store all the expert information is to use random sets; we also show how fuzzy sets naturally appear in such random set representation. We then show how the random set representation can be extended to the general (“fuzzy”) case when, in addition to disagreements, experts are also unsure whether some objects satisfy certain properties or not.

中文翻译：

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如何在计算机系统中完全表示关于不精确属性的专家信息：随机集、模糊集等：概述

为了帮助计算机做出更好的决策，最好用计算机可理解的术语来描述我们的所有知识。这对于用数值描述的知识很容易：我们只是将相应的数字存储在计算机中。这对于了解每个对象为真或假的精确（明确定义）属性也很容易：我们只需将相应的“真”和“假”值存储在计算机中。挑战在于如何存储有关不精确属性的信息。在本文中，我们概述了完全存储有关不精确属性的专家信息的不同方法。我们表明，在最简单的情况下，当不精确的唯一来源是不同专家之间的分歧时，存储所有专家信息的自然方法是使用随机集；我们还展示了模糊集如何自然地出现在这种随机集表示中。然后我们展示了如何将随机集表示扩展到一般（“模糊”）情况，除了分歧之外，专家还不确定某些对象是否满足某些属性。