A Comparison of Axiomatic Approaches to Qualitative Decision Making Using Possibility Theory
Abstract
In this paper we analyze two recent axiomatic approaches proposed by Dubois et al., [5] and by Giang and Shenoy [10] for qualitative decision making where uncertainty is described by possibility theory. Both axiomtizations are inspired by yon Neumann and Morgenstern's system of axioms for the case of probability theory. We show that our approach naturally unifies two axiomatic systems that correspond, respectively, to pessimistic and optimistic decision criteria proposed by Dubois et al. The simplifying unification is achieved by (i) replacing axioms that are supposed to reflect two informational attitudes (uncertainty aversion and uncertainty attraction) by an axiom that imposes order on set of standard lotteries, and (ii) using a binary utility scale in which each utility level is represented by a pair of numbers.
Cite
Text
Giang and Shenoy. "A Comparison of Axiomatic Approaches to Qualitative Decision Making Using Possibility Theory." Conference on Uncertainty in Artificial Intelligence, 2001.Markdown
[Giang and Shenoy. "A Comparison of Axiomatic Approaches to Qualitative Decision Making Using Possibility Theory." Conference on Uncertainty in Artificial Intelligence, 2001.](https://mlanthology.org/uai/2001/giang2001uai-comparison/)BibTeX
@inproceedings{giang2001uai-comparison,
title = {{A Comparison of Axiomatic Approaches to Qualitative Decision Making Using Possibility Theory}},
author = {Giang, Phan Hong and Shenoy, Prakash P.},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {2001},
pages = {162-170},
url = {https://mlanthology.org/uai/2001/giang2001uai-comparison/}
}