Decision quality using ranked attribute weights
Management Science
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Foundations of multi-agent systems
Decision Analysis
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MDAI '09 Proceedings of the 6th International Conference on Modeling Decisions for Artificial Intelligence
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Decision Analysis
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This paper presents a method to assign utility values when only partial information is available about the decision makers preferences. We introduce the notion of a utility density function and a maximum entropy principle for utility assignment. The maximum entropy utility solution embeds a large family of utility functions that includes the most commonly used functional forms. We discuss the implications of maximum entropy utility on the preference behavior of the decision maker and present an application to competitive bidding situations where only previous decisions are observed by each party. We also present minimum cross entropy utility, which incorporates additional knowledge about the shape of the utility function into the maximum entropy formulation, and work through several examples to illustrate the approach.