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Efficient Reasoning in Qualitative Probabilistic Networks
- In Proceedings of the 11th National Conference on Artificial Intelligence (AAAI--93
, 1993
"... Qualitative Probabilistic Networks (QPNs) are an abstraction of Bayesian belief networks replacing numerical relations by qualitative influences and synergies [ Wellman, 1990b ] . To reason in a QPN is to find the effect of new evidence on each node in terms of the sign of the change in belief (incr ..."
Abstract
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Cited by 68 (9 self)
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Qualitative Probabilistic Networks (QPNs) are an abstraction of Bayesian belief networks replacing numerical relations by qualitative influences and synergies [ Wellman, 1990b ] . To reason in a QPN is to find the effect of new evidence on each node in terms of the sign of the change in belief
Uncertainty and Decisions in Medical Informatics
, 1995
"... Characterizations of Decision Analytic Models Restricting reasoning to only the structure of influence diagrams yields models that may be too weak to make many decisions of interest. A few research efforts have explored intermediate levels of representation that give more than simply structure but ..."
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but demand less than full numbers. Wellman [38] defines qualitative influences among random variables in terms of stochastic dominance of their distribution functions, and defines a qualitative version of synergy and anti-synergy among joint influences on a variable. Because these definitions capture only
