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Combining Second-Or...
Combining Second-Order Belief Distributions with Qualitative Statements in Decision Analysis
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- Caster, Ola (author)
- Stockholms universitet,Institutionen för data- och systemvetenskap,Uppsala Monitoring Centre, Sweden
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- Ekenberg, Love (author)
- Stockholms universitet,Institutionen för data- och systemvetenskap
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(creator_code:org_t)
- 2011-10-17
- 2012
- English.
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In: Managing Safety of Heterogeneous Systems. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783642228834 - 9783642228841 ; , s. 67-87
- Related links:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- There is often a need to allow for imprecise statements in real-world decision analysis. Joint modeling of intervals and qualitative statements as constraint sets is one important approach to solving this problem, with the advantage that both probabilities and utilities can be handled. However, a major limitation with interval-based approaches is that aggregated quantities such as expected utilities also become intervals, which often hinders efficient discrimination. The discriminative power can be increased by utilizing second-order information in the form of belief distributions, and this paper demonstrates how qualitative relations between variables can be incorporated into such a framework. The general case with arbitrary distributions is described first, and then a computationally efficient simulation algorithm is presented for a relevant sub-class of analyses. By allowing qualitative relations, our approach preserves the ability of interval-based methods to be deliberately imprecise. At the same time, the use of belief distributions allows more efficient discrimination, and it provides a semantically clear interpretation of the resulting beliefs within a probabilistic framework.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Systemvetenskap, informationssystem och informatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Information Systems (hsv//eng)
Keyword
- data- och systemvetenskap
- Computer and Systems Sciences
Publication and Content Type
- ref (subject category)
- kap (subject category)
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