Accountable classifications without frontiers.

Abstract : This paper addresses the problem of multicriteria ordinal sorting through the lens of accountability, the ability of a human decision maker to own a recommendation made by the system. It proposes a number of model features that would favor the capability to support the recommendation with a convincing explanation, builds the only model possessing them all, discusses its aptitude at correctly representing some given preference information, and thoroughly describes the output recommendation, from mathematical and computational points of view. This recommendation is supported by an explanation, that takes the form of arguments implementing some specific argument schemes. Finally, it uncovers some flaws of the model, analyses their consequences, and proposes several directions for future research.
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https://hal.archives-ouvertes.fr/hal-01956134
Contributor : Wassila Ouerdane <>
Submitted on : Friday, December 14, 2018 - 9:25:38 PM
Last modification on : Tuesday, October 15, 2019 - 6:54:03 AM

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  • HAL Id : hal-01956134, version 1

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Khaled Belahcene, Christophe Labreuche, Nicolas Maudet, Vincent Mousseau, Wassila Ouerdane. Accountable classifications without frontiers.. The EURO mini conference from multiple criteria Decision Aiding to Preference Learning (DA2PL'16), Nov 2016, Paderborn, Germany. ⟨hal-01956134⟩

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