Uncertain logical gates in possibilistic networks: Theory and application to human geographyReport as inadecuate




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1 IRIT - Institut de recherche en informatique de Toulouse 2 ESPACE - Étude des Structures, des Processus d’Adaptation et des Changements de l’Espace 3 SPARKS - Scalable and Pervasive softwARe and Knowledge Systems 4 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics CRISAM - Inria Sophia Antipolis - Méditerranée , SPARKS - Scalable and Pervasive softwARe and Knowledge Systems

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. The elicitation of probability tables by experts is made much easier by means of noisy logical gates that enable multidimensional tables to be constructed from the knowledge of a few parameters. This paper presents the possibilistic counterparts of usual noisy connectives and, or, max, min,. .

Their interest and limitations are illustrated on an example taken from a human geography model-ing problem. The difference of behavior between probabilistic and possibilistic connectives is discussed in detail. Results in this paper may be useful to bring possibilistic networks closer to applications.

Keywords : possibility theory belief networks noisy gates expert knowledge human geography





Author: Didier Dubois - Giovanni Fusco - Henri Prade - Andrea G. B. Tettamanzi -

Source: https://hal.archives-ouvertes.fr/



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