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Second-Order Risk Constraints in Decision Analysis
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
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.
2014 (English)In: Axioms, ISSN 2075-1680, Vol. 3, no 1, 31-45 p.Article in journal (Refereed) Published
Abstract [en]

Recently, representations and methods aimed at analysing decision problems where probabilities and values (utilities) are associated with distributions over them (second-order representations) have been suggested. In this paper we present an approach to how imprecise information can be modelled by means of second-order distributions and how a risk evaluation process can be elaborated by integrating procedures for numerically imprecise probabilities and utilities. We discuss some shortcomings of the use of the principle of maximising the expected utility and of utility theory in general, and offer remedies by the introduction of supplementary decision rules based on a concept of risk constraints taking advantage of second-order distributions.

Place, publisher, year, edition, pages
2014. Vol. 3, no 1, 31-45 p.
Keyword [en]
decision analysis, second-order information, risk analysis, risk constraints
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-108646DOI: 10.3390/axioms3010031OAI: oai:DiVA.org:su-108646DiVA: diva2:759839
Available from: 2014-10-31 Created: 2014-10-31 Last updated: 2014-11-27Bibliographically approved

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Ekenberg, LoveDanielson, MatsLarsson, AronSundgren, David
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