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Directed evidential networks with conditional belief functions. (English) Zbl 1274.68515
Nielsen, Thomas Dyhre (ed.) et al., Symbolic and quantitative approaches to reasoning with uncertainty. 7th European conference, ECSQARU 2003, Aalborg, Denmark, July 2–5, 2003. Proceedings. Berlin: Springer (ISBN 3-540-40494-5/pbk). Lect. Notes Comput. Sci. 2711, 291-305 (2003).
Summary: The main question addressed in this paper is how to represent belief functions independencies by graphical model. Directed evidential networks (DEVNs) with conditional belief functions are then proposed. These networks are directed acyclic graphs (DAGs) similar to Bayesian networks but instead of using probability functions, we use belief functions. Directed evidential network with conditional belief functions has the advantage of providing an appropriate representation of the knowledge that can be produced as conditional relationships.
For the entire collection see [Zbl 1029.00059].

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