Implementing Second-Order Decision Analysis: Concepts, Algorithms, and Tool

• Main Authors: Aron Larsson, Alina Kuznetsova, Ola Caster, Love Ekenberg
• Format: Article
• Language: English
• Published: Asia University 2014-01-01
• Series: Advances in Decision Sciences
• Online Access: http://dx.doi.org/10.1155/2014/519512

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.