Implementing Second-Order Decision Analysis: Concepts, Algorithms, and Tool
2014 (English)In: Advances in Decision Sciences, ISSN 2090-3359, E-ISSN 2090-3367, 519512Article in journal (Refereed) Published
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.
Place, publisher, year, edition, pages
Decision analysis, imprecise information, second-order probability, decision tool
Research subject Computer and Systems Sciences
IdentifiersURN: urn:nbn:se:su:diva-110999DOI: 10.1155/2014/519512OAI: oai:DiVA.org:su-110999DiVA: diva2:773773