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Granularity as an Optimal Approach to Uncertainty - A General Mathematical Idea with Applications to Sleep, Consumption, Traffic Control, Learning, etc.

机译:粒度作为不确定性的最优方法 - 一种应用于睡眠,消费,交通控制,学习等的一般数学思想

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摘要

Traditional statistical and fuzzy approaches to describing uncertainty are continuous in the sense that we use a (potentially infinite) set of values from the interval [0,1] to characterize possible degrees of uncertainty. In reality, experts describe their degree of belief by using one of the finitely many words from natural language; in this sense, the actual description of expert uncertainty is granular.In this paper, we show that in some reasonable sense, granularity is the optimal way of describing uncertainty. A similar mathematical idea explains similar u22granularityu22 in such diverse areas as sleep, consumption, traffic control, and learning.
机译:在描述不确定性方面,传统的统计和模糊方法是连续的,因为我们使用间隔[0,1]中的一组(可能无限)值来表征可能的不确定性程度。实际上,专家通过使用自然语言中有限的多个词之一来描述他们的信仰程度。从这个意义上讲,专家不确定性的实际描述是粒度化的。本文表明,在某种合理的意义上,粒度是描述不确定性的最佳方法。一个类似的数学思想解释了在睡眠,消费,交通控制和学习等各个领域中类似的粒度。

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