Christophe LABREUCHE Researcher at Thales Research & Technology, Palaiseau France.
Title: Explanation in multi-criteria decision making: why and how?
Abstract:
Multi-Criteria Decision Aid (MCDA) aims at helping an individual to make choices among alternatives described by several attributes, from a (small) set of learning data representing her preferences. MCDA has a wide range of applications in smart cities, public policy assessment, recommender systems and so on. Among the variety of available decision models, one can cite the weighted majority, additive utility, weighted sum or the Choquet integral.
A trend in Artificial Intelligence and other domains is that decision support is not a black box but rather should explain its recommendation. The difficulty is to explain the result of decision models that are more and more elaborate. We will review some existing explanatory approaches for several multi-criteria decision models. Depending on the application needs, the sought explanation can take the form of some kind of proof, or on the opposite, be more simply provide some insights on the main arguments.
Biography:
Christophe Labreuche received a graduate engineer diploma from Ecole Centrale de Lyon (1993) and the PhD degree in applied mathematics from University of Paris Dauphine (1997). He has been working in more than 15 years in decision theory, and especially in multi-criteria decision making, argumentation, game theory, automated negotiation, automated decision making, application to software and system engineering. He applied these techniques and especially multi-criteria approach to industrial applications in the domains of homeland security, defence, crisis management, transport and satellites. Since 2014, he has been Associate Editor of the international journal IEEE – Transactions on Fuzzy Systems.
