Ranking Alternatives on the Basis of Generic Constraints and Examples - A Possibilistic Approach
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 393-397.
Abstract
The paper presents and discusses a method for rank-ordering alternatives on the basis of constraints induced by generic principles (expressing for instance the relative importance of criteria), or by examples of orderings between particular alternatives, without resorting to the use of an aggregation operation for evaluating the alternatives. The approach, which remains qualitative, is based on the minimal specificity principle of possibility theory in order to complete the constraints. It is compared on an illustrative example to an aggregation-based approach using Choquet integral. The way constraints expressed in the Choquet integral setting translate into constraints in the proposed approach is discussed.
@inproceedings{ijcai2007p61,
title = {Ranking Alternatives on the Basis of Generic Constraints and Examples - A Possibilistic Approach},
author = {Gérard, Romain and Kaci, Souhila and Prade, Henri},
booktitle = {Proceedings of the Twentieth International Joint Conference on
Artificial Intelligence, {IJCAI-07}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ramon López de Mántaras},
pages = {393--397},
year = {2007},
url = {https://ijcai.org/proceedings/2007/61},
}
TY - CPAPER TI - Ranking Alternatives on the Basis of Generic Constraints and Examples - A Possibilistic Approach AU - Gérard, Romain AU - Kaci, Souhila AU - Prade, Henri T2 - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 PB - International Joint Conferences on Artificial Intelligence PY - 2007 SP - 393 EP - 397 UR - https://ijcai.org/proceedings/2007/61 ER -Copied
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