Ranking Alternatives on the Basis of Generic Constraints and Examples - A Possibilistic Approach

Ranking Alternatives on the Basis of Generic Constraints and Examples - A Possibilistic Approach
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基于通用约束和示例对备选方案进行排名 - 一种可能性方法

DOI:
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发表时间:
2007
期刊:
International Joint Conference on Artificial Intelligence
影响因子:
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通讯作者:
H. Prade
H. Prade
中科院分区:
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文献类型:
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作者:
Romain Gérard;S. Kaci;H. Prade

文献摘要

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本文提出并讨论了一种基于通用原则(例如表示标准的相对重要性)引起的约束或通过特定备选方案之间的排序示例对备选方案进行排名排序的方法,而无需使用聚合操作来评估备选方案。该方法仍然是定性的,基于可能性理论的最小特异性原则,以完成约束。通过示例将其与使用 Choquet 积分的基于聚合的方法进行比较。讨论了 Choquet 积分设置中表达的约束转化为所提出方法中的约束的方式。
The paper presents and discusses a method for rank-ordering alternatives on the basis of constraints induced by generic principles (expressing for instance the relative importance of criteria), or by examples of orderings between particular alternatives, without resorting to the use of an aggregation operation for evaluating the alternatives. The approach, which remains qualitative, is based on the minimal specificity principle of possibility theory in order to complete the constraints. It is compared on an illustrative example to an aggregation-based approach using Choquet integral. The way constraints expressed in the Choquet integral setting translate into constraints in the proposed approach is discussed.