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On the analysis of probability-possibility transformations: changing operations and graphical models. (English) Zbl 06507023
Destercke, Sébastien (ed.) et al., Symbolic and quantitative approaches to reasoning with uncertainty. 13th European conference, ECSQARU 2015, Compiègne, France, July 15–17, 2015. Proceedings. Cham: Springer (ISBN 978-3-319-20806-0/pbk; 978-3-319-20807-7/ebook). Lecture Notes in Computer Science 9161. Lecture Notes in Artificial Intelligence, 279-289 (2015).
Summary: Representing and reasoning with uncertain information is a common topic in Artificial Intelligence. In this paper, we focus on probability-possibility transformations in the context of changing operations and graphical models. Existing works mainly propose probability-possibility transformations satisfying some desirable properties. Regarding the analysis of the behavior of these transformations with respect to changing operations (such as conditioning and marginalization), only few works addressed such issues. This paper concerns the commutativity of transformations with respect to some reasoning tasks such as marginalization and conditioning. Another crucial issue addressed in this paper is the one of probability-possibility transformations in the context of graphical models, especially the independence of events and variables.
For the entire collection see [Zbl 1316.68008].

MSC:
68T37 Reasoning under uncertainty in the context of artificial intelligence
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