A generic framework to include Belief functions in preference handling for multi-criteria decision

Sébastien Destercke (1)

1 Heudiasyc - Heuristique et Diagnostic des Systèmes Complexes [Compiègne]

Modelling the preferences of a decision maker about multi-criteria alternatives usually starts by collecting preference information, then used to fit a model issued from a set of hypothesis (weighted average, CP-net). This can lead to inconsistencies, due to inaccurate information provided by the decision maker or to a poor choice of hypothesis set. We propose to quantify and resolve such inconsistencies, by allowing the decision maker to express her/his certainty about the provided preferential information in the form of belief functions.

Domaines: Intelligence artificielle [cs.AI]

Sébastien Destercke. A generic framework to include Belief functions in preference handling for multi-criteria decision. 14th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2017), Jun 2017, Lugano, Switzerland. pp.179-189. ⟨hal-01677517⟩