On reasoning in networks with qualitative uncertainty

UAI'93 Proceedings of the Ninth international conference on Uncertainty in artificial intelligence(2013)

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摘要
In this paper some initial work towards a new approach to qualitative reasoning under uncertainty is presented. This method is not only applicable to qualitative probabilistic reasoning, as is the case with other methods, but also allows the qualitative propagation within networks of values based upon possibility theory and Dempster-Shafer evidence theory. The method is applied to two simple networks from which a large class of directed graphs may be constructed. The results of this analysis are used to compare the qualitative behaviour of the three major quantitative uncertainty handling formalisms, and to demonstrate that the qualitative integration of the formalisms is possible under certain assumptions.
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关键词
large class,major quantitative uncertainty handling,certain assumption,initial work,possibility theory,qualitative propagation,qualitative uncertainty,probabilistic reasoning,dempster-shafer evidence theory,qualitative integration,qualitative behaviour,directed graph,dempster shafer,qualitative reasoning
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