March 31, 2003
A fundamental step in decision analysis is the elicitation of the decision‐maker’s preferences about the prospects of a decision situation in the form of utility values. However, this can be a difficult task to perform in practice as the number of prospects may be large, and eliciting a utility value for each prospect may be a time consuming and stressful task for the decision maker. To relieve some of the burden of this task, this paper presents a normative method to assign unbiased utility values when only incomplete preference information is available about the decision maker. We introduce the notion of a utility density function and propose a maximum entropy utility principle for utility assignment.
Abbas, A. 2002. An Entropy Approach for Utility Assignment in Decision Analysis. In: C. Williams (ed.), Bayesian Inference and Maximum Entropy Methods in Science and Engineering, Moscow ID August 3rd – 7th 2002, AIP Conference Proceedings 659, American Institute of Physics, Melville NY, pp.328-338