Qualitative Decision Making Under Possibilistic Uncertainty: Toward more discriminating criteria

Abstract

The aim of this paper is to propose a generalization of previous approaches in qualitative decision making. Our work is based on the binary possibilistic utility (PU), which is a possibilistic counterpart of Expected Utility (EU).We first provide a new axiomatization of PU and study its relation with the lexicographic aggregation of pessimistic and optimistic utilities. Then we explain the reasons of the coarseness of qualitative decision criteria. Finally, thanks to a redefinition of possibilistic lotteries and mixtures, we present the refined binary possibilistic utility, which is more discriminating than previously proposed criteria.

Appears in Proceedings of the Twenty-First Conference on Uncertainty in Artificial Intelligence (UAI2005)

References in corpus (3)

• Arguing for Decisions: A Qualitative Model of Decision Making
• A Possibilistic Model for Qualitative Sequential Decision Problems under Uncertainty in Partially Observable Environments
• A Comparison of Axiomatic Approaches to Qualitative Decision Making Using Possibility Theory