Abstract
We consider the problem of reasoning with uncertain evidence in Bayesian networks (BN). There are two main cases: the first one, known as virtual evidence, is evidence with uncertainty, the second, called soft evidence, is evidence of uncertainty. The initial inference algorithms in BNs are designed to deal with one or several hard evidence or virtual evidence. Several recent propositions about BN deal with soft evidence, but also with ambiguity and vagueness of the evidence. One of the proposals so far advanced is based on the fuzzy theory and called fuzzy evidence. The original contribution of this paper is to describe the different types of uncertain evidence with the help of a simple example, to explain the difference between them and to clarify the appropriate context of use.
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Ben Mrad, A., Delcroix, V., Maalej, M.A., Piechowiak, S., Abid, M. (2012). Uncertain Evidence in Bayesian Networks: Presentation and Comparison on a Simple Example. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances in Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 299. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31718-7_5
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DOI: https://doi.org/10.1007/978-3-642-31718-7_5
Publisher Name: Springer, Berlin, Heidelberg
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