Patrice Perny Professor at Université Pierre et Marie Curie, LIP6, Paris, France
Title: Adaptive Preference Elicitation for Decision Making with Rank-Dependent Models (*)
Abstract: We present an incremental approach to preference elicitation for interactive decision support with rank-dependent models. This approach is based on an active learning process in which preference queries are selected one at the time in order to efficiently reduce the set of possibly optimal alternatives. The elicitation process is stopped when it can be proved that further specifications of the model cannot seriously challenge the current recommendation. This principle is illustrated in the context of decision making under risk, for the incremental elicitation of the weighting function transforming cumulative probabilities in Yaari's model and RDU. It is also illustrated in the the context of multicriteria decision making, for the incremental elicitation of the capacity in the Choquet integral, modelling the importance attached to all subsets of criteria.
(*) the presentation is based on recent joint works with Nawal Benabbou and Paolo Viappiani at LIP6.
Biography: Patrice Perny received the Ph.D. degree in Computer Science and Operations Research in 1992 from University Paris Dauphine and Habilitation degree in 2000 from University Pierre et Marie Curie (UPMC, Paris 6). He became Associate Professor in 1992 at University Pierre et Marie Curie (UPMC), Paris, France, and full Professor in 2002. He is currently head of the DESIR department at LIP6 (Decision making, Intelligent System and Operations Research). His activities concern preference modeling, multiobjective optimization, decision and optimisation under uncertainty and risk, computational social choice and algorithmic game theory. He works on the elaboration of preference models for decision making, and on the development of algorithms allowing the fast determination of preferred solutions in combinatorial decision problems. The applications concern decision support systems (rational preparation of important human decisions) and automatic decision making (autonomous decision agents).