Name
Abstract | ||
|---|---|---|
In the context of decision under uncertainty, standard gambles are classically used to elicit a utility function on a set X of consequences. The utility of an element x in X is derived from the probability p for which a gamble giving the best outcome in X with probability p and the worst outcome in X otherwise, is indifferent to getting x for sure. In many situations, uncertainty that can be observed on the true value of X concerns only neighbour values. Uncertainty is then represented by a probability distribution whose support is an interval. In this case, standard gambles are unrealistic for the decision maker. We consider uncertainty represented by an equi-probability over an interval of X. This paper addresses the elicitation of a utility function on X by obtaining the certainty equivalent of an equi-probability over an interval of X. We show that not all utility models are suitable to accomplish this task. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-20807-7_3 | Lecture Notes in Artificial Intelligence |
Field | DocType | Volume |
Econometrics,Mathematical economics,Certainty,Computer science,Probability distribution,Artificial intelligence,Machine learning,Decision maker | Conference | 9161 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
4 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christophe Labreuche | 1 | 709 | 65.78 |
| Sébastien Destercke | 2 | 283 | 45.08 |
| Brice Mayag | 3 | 33 | 8.36 |