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Implementing Second-Order Decision Analysis: Concepts, Algorithms, and Tool
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. Mid Sweden University, Sweden.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. Uppsala Monitoring Centre, Sweden.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. International Institute for Applied Systems Analysis, Austria.
2014 (English)In: Advances in Decision Sciences, ISSN 2090-3359, E-ISSN 2090-3367, 519512Article 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
2014. 519512
Keyword [en]
Decision analysis, imprecise information, second-order probability, decision tool
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-110999DOI: 10.1155/2014/519512OAI: oai:DiVA.org:su-110999DiVA: diva2:773773
Available from: 2014-12-19 Created: 2014-12-19 Last updated: 2017-12-05Bibliographically approved

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Larsson, AronCaster, OlaEkenberg, Love
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