Abstract
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.
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Labreuche, C., Maudet, N., Ouerdane, W. (2011). Minimal and Complete Explanations for Critical Multi-attribute Decisions. In: Brafman, R.I., Roberts, F.S., Tsoukiàs, A. (eds) Algorithmic Decision Theory. ADT 2011. Lecture Notes in Computer Science(), vol 6992. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24873-3_10
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DOI: https://doi.org/10.1007/978-3-642-24873-3_10
Publisher Name: Springer, Berlin, Heidelberg
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