Belief structures, possibility theory and decomposable confidence measures on finite sets
Computers and Artificial Intelligence
Nonmonotonic reasoning, preferential models and cumulative logics
Artificial Intelligence
Epistemic entrenchment and possibilistic logic
Artificial Intelligence
What does a conditional knowledge base entail?
Artificial Intelligence
Refinements of the maximin approach to decision-making in a fuzzy environment
Fuzzy Sets and Systems - Special issue on fuzzy optimization
Possibility theory as a basis for qualitative decision theory
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Plausibility measures and default reasoning
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Numerical representations of acceptance
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Generalized qualitative probability: savage revisited
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Logical representation and computation of optimal decisions in a qualitative setting
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
A Logical Analysis of the Relationship between Commitment and Obligation
Journal of Logic, Language and Information
Towards Possibilistic Decision Functions with Minimum-Based Sugeno Integrals
SOFSEM '99 Proceedings of the 26th Conference on Current Trends in Theory and Practice of Informatics on Theory and Practice of Informatics
Artificial Intelligence - Special issue: Fuzzy set and possibility theory-based methods in artificial intelligence
Reference-dependent Qualitative Models for Decision Making under Uncertainty
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Ordinal and probabilistic representations of acceptance
Journal of Artificial Intelligence Research
Qualitative models for decision under uncertainty without the commensurability assumption
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Comparative uncertainty, belief functions and accepted beliefs
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Qualitative decision theory with Sugeno integrals
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Using Possibilistic Logic for Modeling Qualitative Decision: ATMS-based Algorithms
Fundamenta Informaticae
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This paper proposes a method that finds a preference relation on a set of acts from the knowledge of an ordering on events describing the decision-maker's uncertainty and an ordering of consequences of acts, describing the decision maker's preferences. However, contrary to classical approaches to decision theory, this method does not resort to any numerical representation of utility nor uncertainty and is purely ordinal. It is shown that although many axioms of Savage theory can be preserved and despite the intuitive appeal of the ordinal method, the approach is inconsistent with a probabilistic representation of uncertainty. It leads to the kind of uncertainty theory encountered in nonmonotonic reasoning (especially preferential and rational inference). Moreover the method turns out to be either very little decisive or to lead to very risky decisions, although its basic principles look sound. This paper raises the question of the very possibility of purely symbolic approaches to Savage-like decision-making under uncertainty and obtains preliminary negative results.