Choices: an introduction to decision theory
Choices: an introduction to decision theory
A Comparison of Axiomatic Approaches to Qualitative Decision Making Using Possibility Theory
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Conditional plausibility measures and Bayesian networks
Journal of Artificial Intelligence Research
Great expectations: part I: on the customizability of generalized expected utility
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Plausibility measures: a user's guide
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Characterizing and reasoning about probabilistic and non-probabilistic expectation
Journal of the ACM (JACM)
Elicitation and utilization of application-level utility functions
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
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Many different rules for decision making have been introduced in the literature. We show that a notion of generalized expected utility proposed in [F. Chu, J.Y. Halpern, Great expectation. Part I: On the customizability of generalized expected utility, in: Proc. IJCAI-03, Acapulco, Mexico, 2003] is a universal decision rule, in the sense that it can essentially all other decision rules. This approach gives us a general technique for designing new decision rules as well as providing a framework for comparing decision rules to each other.