Implementing second-order decision analysis: concepts, algorithms, and tool

Larsson, A., Kuznetsova, A., Caster, O., & Ekenberg, L. ORCID: https://orcid.org/0000-0002-0665-1889 (2014). Implementing second-order decision analysis: concepts, algorithms, and tool. Advances in Decision Sciences 519512 1-8. 10.1155/2014/519512.

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Abstract

We present implemented concepts and algorithms for a simulation approach to decision evaluation with second-order belief distributions in a common framework for interval decision analysis. The rationale behind this work is that decision analysis with interval-valued probabilities and utilities may lead to overlapping expected utility intervals yielding difficulties in discriminating between alternatives. By allowing for second-order belief distributions over interval-valued utility and probability statements these difficulties may not only be remedied but will also allow for decision evaluation concepts and techniques providing additional insight into a decision problem. The approach is based upon sets of linear constraints together with generation of random probability distributions and utility values from implicitly stated uniform second-order belief distributions over the polytopes given from the constraints. The result is an interactive method for decision evaluation with second-order belief distributions, complementing earlier methods for decision evaluation with interval-valued probabilities and utilities. The method has been implemented for trial use in a user oriented decision analysis software.

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