Implementing Second-Order Decision Analysis: Concepts, Algorithms, and Tool. (27th November 2014)

• Record Type: Journal Article
• Authors: Larsson, Aron; Kuznetsova, Alina; Caster, Ola; Ekenberg, Love
• Other Names: Peiris Shelton Academic Editor.
• Is Part Of: Advances in decision sciences. Volume 2014(2014)
• Publication Date: 2014-11-27
• Subjects: Decision making -- Periodicals; Decision making; Electronic journals; Periodicals; 519
• DOI: 10.1155/2014/519512
• Languages: English
• ISSNs: 2090-3359

Abstract

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.