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The value of additional information in multicriteria decision making choice problems with information imperfections

机译:信息不完善的多准则决策选择问题中附加信息的价值

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摘要

Processing information is a key ingredient for decision making. In most decision-making cases, information is distributed across various sources that may differ in reliability and accuracy. Various sources and kinds of uncertainty are encountered in the same decision situation. "Information imperfections" is a general term that encompasses all kinds of "deficiencies" (such as uncertainty, imprecision, ambiguity, incompleteness) that may affect the quality of information at hand. In discrete multicriteria decision making, where several alternatives are assessed according to heterogeneous and conflicting criteria, information used to assess such alternatives can also be imperfect. It is rather natural, in such a context, to seek additional information to reduce these imperfections. This paper aims at extending the Bayesian model for assessing the value of additional information to multicriteria decision analysis in a context of imperfect information. A unified procedure for processing additional information has been proposed in a previous work. It leads to prior and posterior global preference relational systems. It will be extended here to include pre-posterior analysis where concepts such as the expected value of perfect information and the expected value of imperfect information are adapted to multicriteria decision making choice problems.
机译:处理信息是决策的关键要素。在大多数决策情况下,信息会分布在可靠性和准确性可能不同的各种来源中。在同一决策情况下会遇到各种来源和各种不确定性。 “信息缺陷”是一个通用术语,涵盖可能影响手头信息质量的所有各种“缺陷”(例如不确定性,不精确性,歧义性,不完整性)。在离散的多准则决策中,根据异类和冲突的准则评估了多个备选方案,用于评估此类备选方案的信息也可能是不完善的。在这种情况下,寻求更多信息以减少这些缺陷是很自然的。本文旨在扩展贝叶斯模型,以在不完全信息的情况下评估附加信息对多准则决策分析的价值。在先前的工作中已经提出了用于处理附加信息的统一程序。它导致先验和后验全局偏好关系系统。这里将扩展为包括后验分析,其中将诸如完美信息的期望值和不完美信息的期望值之类的概念用于多准则决策选择问题。

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