BOURDACHE Nadjet

Dottore di ricerca
Gruppo di ricerca : DECISION
Data di partenza : 12/16/2020
https://lip6.fr/Nadjet.Bourdache

Relatore : Patrice PERNY, Olivier SPANJAARD

Élicitation incrémentale des préférences pour l'optimisation multi-objectifs : modèles non-linéaires, domaines combinatoires et approches tolérantes aux erreurs

This thesis work falls within the area of algorithmic decision theory, a research domain at the crossroad of decision theory, operations research and artificial intelligence. The aim is to produce interactive optimization methods based on incremental preference elicitation in decision problems involving several criteria, opinions of agents or scenarios. Preferences are represented by general decision models whose parameters must be adapted to each decision problem and each decision maker.
Our methods interleave the elicitation of parameters and the exploration of the solution space in order to determine the optimal choice for the decision maker. The idea behind this is to use information provided by the elicitation to guide the exploration of the solution space and vice versa. In this thesis, we introduce new incremental elicitation methods for decision making in different contexts$!!$: first for decision making in combinatorial domains when the decision models are non-linear, and then in a setting where one takes into account the possibility of inconsistencies in the answers of te decision maker. All the algorithms that we introduce are general and can be applied to a wide range of multiobjective decision problems.

Difesa : 12/16/2020

Membri della commissione :

DESTERCKE Sébastien (Chargé de recherche CNRS/ Université de Technologie de Compiègne) [Rapporteur]
MOUSSEAU Vincent (Professeur/ CentralSupélec) [Rapporteur]
GONZALES Christophe (Professeur/ Aix Marseille Université)
ÖZTÜRK Meltem (Maître de conférences/ Université Paris Dauphine)
MARSALA Christophe (Professeur/ Sorbonne Université)
PERNY Patrice (Professeur/ Sorbonne Université)
SPANJAARD Olivier (Maître de conférences/ Sorbonne Université)

Data di partenza : 12/16/2020

Pubblicazioni 2017-2020

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