Qualitative Decision Making Under Possibilistic Uncertainty: Toward more discriminating criteria
Artificial Intelligence
2012-07-09 v1 Computer Science and Game Theory
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.
Keywords
Cite
@article{arxiv.1207.1425,
title = {Qualitative Decision Making Under Possibilistic Uncertainty: Toward more discriminating criteria},
author = {Paul Weng},
journal= {arXiv preprint arXiv:1207.1425},
year = {2012}
}
Comments
Appears in Proceedings of the Twenty-First Conference on Uncertainty in Artificial Intelligence (UAI2005)