Abstract
This paper deals with belief graphical models and probability-possibility transformations. It first analyzes some properties of transforming a credal network into a possibilistic one. In particular, we are interested in satisfying some properties of probability possibility transformations like dominance and order preservation. The second part of the paper deals with using probability possibility transformations in order to perform MAP inference in credal networks. This problem is known for its high computational complexity in comparison with MAP inference in Bayesian and possibilistic networks. The paper provides preliminary experimental results comparing our approach with both exact and approximate inference in credal networks.
| Original language | English |
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| Title of host publication | Proceedings of the 9th International Conference on Scalable Uncertainty Management (SUM’15), 2015. |
| Place of Publication | Quebec, Canada |
| Number of pages | 14 |
| Publication status | Published - 2015 |
| Event | 9th International Conference on Scalable Uncertainty Management - Quebec City, Canada Duration: 16 Sept 2015 → 18 Sept 2015 http://www.fernuni-hagen.de/wbs/sum2015/index.php |
Conference
| Conference | 9th International Conference on Scalable Uncertainty Management |
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| Abbreviated title | SUM 2015 |
| Country/Territory | Canada |
| City | Quebec City |
| Period | 16/09/15 → 18/09/15 |
| Internet address |