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Preference elicitation and learning in a Multiple Criteria Decision Analysis perspective
Intervenant(s) : Pr. Marc PirlotIn this talk, we shall first sketch the way different communities look at preference learning and contrast them with the peculiarities of Multiple Criteria Decision Analysis. We then mainly focus on the inter-relations with the Machine Learning community, aiming to identify what are the issues we have in common and what can be learned from them in a Decision Analysis perspective. We illustrate the commonalities and discrepancies between both approaches by presenting some recent research works. The last part of the talk will propose and describe four research avenues which we see as structuring the recent and forthcoming efforts regarding preference elicitation and learning in the field of multiple criteria decision analysis. In these four trends, the interactions with disciplines such as Optimization, Artificial Intelligence and Machine Learning are likely to become increasingly important.
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