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Implementing Second-Order Decision Analysis: Concepts, Algorithms, and Tool
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. Department of Computer and Systems Sciences, Stockholm University, Postbox 7003, Kista, Sweden . (Computational Industrial Engineering)ORCID iD: 0000-0003-0310-0018
Institute for Information Processing, Leibniz University, Hannover, Germany.
ciences, Stockholm University, Postbox 7003, Kista, Sweden .
ciences, Stockholm University, Postbox 7003, Kista, Sweden .
2014 (English)In: Advances in Decision Sciences, ISSN 2090-3359, E-ISSN 2090-3367, Art. no. 519512- p.Article in journal (Refereed) Published
Abstract [en]

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
Hindawi Publishing Corporation, 2014. Art. no. 519512- p.
Keyword [en]
Decision analysis, imprecise information, second-order probability, decision tool
National Category
Computer Science
URN: urn:nbn:se:miun:diva-23556DOI: 10.1155/2014/519512ScopusID: 2-s2.0-84918586059OAI: diva2:767178
Available from: 2014-12-01 Created: 2014-12-01 Last updated: 2016-10-25Bibliographically approved

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