Abstract
In this paper, we develop a qualitative theory of influence diagrams that can be used to model and solve sequential decision making tasks when only qualitative (or imprecise) information is available. Our approach is based on an orderof-magnitude approximation of both probabilities and utilities and allows for specifying partially ordered preferences via sets of utility values. We also propose a dedicated variable elimination algorithm that can be applied for solving order-of-magnitude influence diagrams.
| Original language | English |
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| Title of host publication | Proceedings of the 27th Conference on Uncertainty in Artificial Intelligence, UAI 2011 |
| Publisher | AUAI Press |
| Pages | 489-496 |
| Number of pages | 8 |
| Publication status | Published - 2011 |
Publication series
| Name | Proceedings of the 27th Conference on Uncertainty in Artificial Intelligence, UAI 2011 |
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