École Nationale Supérieure de
Techniques Avancées

Abstract

The outbreak of the Covid-19 crisis has exposed the deficiency of some healthcare systems and the lack of essential medical resources such as ICU beds and ventilators. The allocation of these scarce resources is a critical question involving high stakes, and decision makers, namely doctors, face a huge responsibility when picking the patients, supposed to be flowing in numbers exceeding the capacity of the medical facilities, to have access to them. In this work, we tackle this issue by introducing a novel decision aiding framework by extending the multi-winner voting theory, where a limited target size of candidates is to be elected, to contexts where the voters are not substitutable, but are rather experts basing their assessments on underlying criteria. We also set up a method for the elicitation of the parameters describing the relative importance of different groups of voters. The main contribution of the first part is the generalization of numerous common multi-winner voting schemes to non-anonymous versions and the discussion of some of their normative and computational properties. As for the second part, tools from multi-criteria optimization and Dempster-Shafer thory, a generalization of probability theory, are put together to define a general method for modeling the weights of sets of experts with different specialties.