Handbook of logic in artificial intelligence and logic programming (vol. 3)
Axiomatic Foundations for Qualitative/Ordinal Decisions with Partial Preferences
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
On the axiomatization of qualitative decision criteria
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Arguing for decisions: a qualitative model of decision making
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Advances in Qualitative Decision Theory: Refined Rankings
IBERAMIA-SBIA '00 Proceedings of the International Joint Conference, 7th Ibero-American Conference on AI: Advances in Artificial Intelligence
Qualitative decision under uncertainty: back to expected utility
Artificial Intelligence
On possibilistic case-based reasoning for selecting partners for multi-attribute agent negotiation
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Weakening the commensurability hypothesis in possibilistic qualitative decision theory
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Qualitative decision under uncertainty: back to expected utility
Artificial Intelligence
On possibilistic case-based reasoning for selecting partners in multi-agent negotiation
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
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A qualitative counterpart to Von Neumann and Morgenstern's Expected Utility Theory of decision under uncertainty was recently proposed by Dubois and Prade. In this model, belief states are represented by normalised possibility distributions over an ordinal scale of plausibility, and the utility (or preference) of consequences of decisions are also measured in an ordinal scale. In this paper we extend the original Dubois and Prade's decision model to cope with partially inconsistent descriptions of belief states, represented by non-normalised possibility distributions. Subnormal possibility distributions frequently arise when adopting the possibilistic model for case-based decision problems. We consider two qualitative utility functions, formally similar to the original ones up to modifying factors coping with the inconsistency degree of belief states. We provide axiomatic characterizations of the preference orderings induced by these utility functions.