Antonucci, Alessandro and De Campos, Cassio Polpo and Huber, David and Zaffalon, Marco (2015) Approximate credal network updating by linear programming with applications to decision making. International Journal of Approximate Reasoning, 58. 25 - 38. ISSN 0888-613X
Full text not available from this repository.Abstract
Credal nets are probabilistic graphical models which extend Bayesian nets to cope with sets of distributions. An algorithm for approximate credal network updating is presented. The problem in its general formulation is a multilinear optimization task, which can be linearized by an appropriate rule for fixing all the local models apart from those of a single variable. This simple idea can be iterated and quickly leads to accurate inferences. A transformation is also derived to reduce decision making in credal networks based on the maximality criterion to updating. The decision task is proved to have the same complexity of standard inference, being NPPP-complete for general credal nets and NP-complete for polytrees. Similar results are derived for the E-admissibility criterion. Numerical experiments confirm a good performance of the method.
| Item Type: | Scientific journal article, Newspaper article or Magazine article |
|---|---|
| Additional Information: | Special Issue of the Twelfth European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2013) |
| Uncontrolled Keywords: | Credal networks; Bayesian networks; Linear programming; Decision making; Maximality; E-admissibility |
| Subjects: | Computer sciences > Artificial intelligence |
| Department/unit: | Dipartimento tecnologie innovative > Istituto Dalle Molle di studi sull’intelligenza artificiale USI-SUPSI |
| Depositing User: | David Huber |
| Date Deposited: | 24 Aug 2015 05:18 |
| Last Modified: | 26 Jul 2016 14:57 |
| URI: | http://repository.supsi.ch/id/eprint/6623 |
Actions (login required)
 |
View Item |