The ability to provide explanations along with recommended decisions to the user is a key feature of decision-aiding tools. We address the question of providing minimal and complete explanations, a problem relevant in critical situations where the stakes are very high. More specifically, we are after explanations with minimal cost supporting the fact that a choice is the weighted Condorcet winner in a multi-attribute problem. We introduce different languages for explanation, and investigate the problem of producing minimal explanations with such languages. © 2011 Springer-Verlag.
CITATION STYLE
Labreuche, C., Maudet, N., & Ouerdane, W. (2011). Minimal and complete explanations for critical multi-attribute decisions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6992 LNAI, pp. 121–134). Springer Verlag. https://doi.org/10.1007/978-3-642-24873-3_10
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