Decision making under measure-based granular uncertainty
Decision making under measure-based granular uncertainty
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DOI：
10.1007/s41066-017-0075-0
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发表时间：
2018-01
影响因子：
5.5
通讯作者：
R. Yager
中科院分区：
文献类型：
--
作者：
R. Yager
在不确定变量在大空间中取值的情况下，我们可以使用空间的粒度来简化知识获取过程。然而，我们观察到，这种使用粒化的代价是在相关的决策过程中引入不精确性。我们注意到，关于与原始空间相关的值的问题的答案通常只能使用区间值来回答。我们看两类决策问题，相关变量的不确定性信息表示间接通过相关颗粒对象的不确定性信息。为了做出精确的决策，我们需要决策者提供一些主观偏好信息，以解决由粒度引起的区间不确定性。在本文中，我们的主要贡献是，我们提供了一种方法来面对不确定性的不确定性信息表示在一个空间的颗粒状物体和基本的不确定性是最普遍的措施表示。
In situations, where an uncertain variable takes its value in a large space, we can use granulation of the space to simplify the knowledge acquisition process. We observe, however, that this use of granulation can come at the price of introducing imprecision into the related decision process. We note that answers to questions about values related to the original space can often only be answered using interval values. We look at two classes of decision problems where uncertain information about relevant variables is expressed indirectly via information about the uncertainty on related granular objects. To make a precise decision, we require the decision maker to provide some subjective preference information to resolve the interval uncertainty induced by the granulation. In this paper, our major contribution is that we provide an approach to decision making in the face of uncertainty where the uncertain information is expressed on a space of granular objects and the underlying uncertainty is most generally represented by a measure.