Explaining robust additive utility models by sequences of preference swaps
Ecole Centrale de Paris（巴黎中央理工学院）；Thales Research & Technology（泰雷兹研究与技术公司）；Université Paris-6（巴黎第六大学）
英文摘要：
Multicriteria decision analysis aims at supporting a person facing a decision problem involving conflicting criteria. We consider an additive utility model which provides robust conclusions based on preferences elicited from the decision maker. The recommendations based on these robust conclusions are even more convincing if they are complemented by explanations. We propose a general scheme, based on sequence of preference swaps, in which explanations can be computed. We show first that the length of explanations can be unbounded in the general case. However, in the case of binary reference scales, this length is bounded and we provide an algorithm to compute the corresponding explanation.
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