Belief structures, possibility theory and decomposable confidence measures on finite sets
Computers and Artificial Intelligence
An introduction to possibilistic and fuzzy logics
Readings in uncertain reasoning
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
A Qualitative Linear Utility Theory for Spohn's Theory of Epistemic Beliefs
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
A Comparison of Axiomatic Approaches to Qualitative Decision Making Using Possibility Theory
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Algebraic Markov decision processes
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Plausibility measures: a user's guide
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
An Axiomatization of Conditional Possibilistic Preference Functionals
ECSQARU '07 Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
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Binary possibilistic utility unifies two previously proposed qualitative decision models: optimistic and pessimistic utilities. All these decision models have been axiomatized in a von Neumann-Morgenstern setting. These axiomatizations have shown the formal similarity of these qualitative utilities and expected utility. Unfortunately in this framework, the representation of uncertainty has to be clearly assumed to be given. In a more general setting, without this restriction, optimistic and pessimistic utilities have been axiomatized à la Savage. This paper proposes a study of the axiomatics of binary possibilistic utility in a Savagean framework.