Uncertain Logical Gates in Possibilistic Networks. An Application to Human Geography

Abstract : Possibilistic networks offer a qualitative approach for modeling epistemic uncertainty. Their practical implementation requires the specification of conditional possibility tables, as in the case of Bayesian networks for probabilities. This paper presents the possibilistic counterparts of the noisy probabilistic connectives (and, or, max, min, . . . ). Their interest is illustrated on an example taken from a human geography modeling problem. The difference of behaviors in some cases of some possibilistic connectives, with respect to their probabilistic analogs, is discussed in details.
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Christoph Beierle; Alex Dekhtyar. Scalable Uncertainty Management, Sep 2015, Québec, QC, Canada. Springer, Lecture Notes in Artificial Intelligence, 9310, pp.249-263, 2015, Scalable Uncertainty Management - 9th International Conference, SUM 2015, Québec City, QC, Canada, September 16–18, 2015. Proceedings. <10.1007/978-3-319-23540-0_17>
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Dernière modification le : jeudi 10 mars 2016 - 01:10:50
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Didier Dubois, Giovanni Fusco, Henri Prade, Andrea G. B. Tettamanzi. Uncertain Logical Gates in Possibilistic Networks. An Application to Human Geography. Christoph Beierle; Alex Dekhtyar. Scalable Uncertainty Management, Sep 2015, Québec, QC, Canada. Springer, Lecture Notes in Artificial Intelligence, 9310, pp.249-263, 2015, Scalable Uncertainty Management - 9th International Conference, SUM 2015, Québec City, QC, Canada, September 16–18, 2015. Proceedings. <10.1007/978-3-319-23540-0_17>. <hal-01203515>

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