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Questionable stepwise explanations for a robust additive preference model
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AI
DOI：10.1016/j.ijar.2023.108982.png)
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Abstract
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In this paper, we study Multiple Criteria Decision Aiding (MCDA) problems modeled using an additive value function. We consider an epistemic framework in which the preferences of the decision-maker are imprecisely specified, yielding a robust additive preference model. In this context, we are interested in explaining recommendations derived from such robust model using a transitive sequence of preference swaps. Previous work laid the foundations for explaining the necessary preference relation through a sequence of necessary preference swaps. We extend this to take into account non-necessary preference, yielding to so-called questionable explanations: a chain of alternatives which is nonincreasing w.r.t. preference of the decision-maker. This approach provides additional descriptive power for explaining robust recommendations. We propose an efficient resolution engine based on Mixed-Integer Linear Programs, and we conduct numerical experiments to assess the benefit of our explanation strategy. (c) 2023 Elsevier Inc. All rights reserved.
Keywords:
Additive utility model
Necessary preference relation
Explanation
MILP
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