It is often recognised that in real-life decision situations, classical utility theory puts too strong requirements on the decision-maker. Various interval approaches for decision making have therefore been developed and these have been reasonably successful. However, a problem that sometimes appears in real-life situations is that the result of an evaluation still has an uncertainty about which alternative is to prefer. This is due to expected utility overlaps rendering discrimination more difficult. In this article we discuss how adding second-order information may increase a decision-maker’s understanding of a decision situation when handling aggregations of imprecise representations, as is the case in decision trees or influence diagrams.
Keywords. Decision analysis, Imprecise probabilities, Imprecise utilities, Hierarchical models
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Authors addresses:
Love Ekenberg
Dept. of Computer and Systems Sciences
Stockholm University
Forum 100,
SE-164 40, Kista,
SWEDEN
Mats Danielson
Electrum 230
SE-164 40 Kista
Mikael Andersson
Dept. of Mathematical Statistics
Stockholm University
SE-106 91 Stockholm
Sweden
Aron Larsson
SE-851 70 Sundsvall
E-mail addresses:
| Love Ekenberg | lovek@dsv.su.se |
| Mats Danielson | mad@dsv.su.se |
| Mikael Andersson | mikaela@math.su.se |
| Aron Larsson | aron.larsson@miun.se |