Context-specific sign-propagation in qualitative probabilistic networks

Authors:
Silja Renooij;Linda C. van der Gaag;Simon Parsons
Affiliations:
Institute of Information and Computing Sciences, Utrecht University, P.O. Box 80.089, 3508 TB Utrecht, Netherlands;Institute of Information and Computing Sciences, Utrecht University, P.O. Box 80.089, 3508 TB Utrecht, Netherlands;Massachussetts Institute of Technology, Sloan School of Management, 3 Cambridge Center, NE20-336 Cambridge, MA
Venue:
Artificial Intelligence
Year:
2002

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Abstract

Qualitative probabilistic networks are qualitative abstractions of probabilistic networks, summarising probabilistic influences by qualitative signs. As qualitative networks model influences at the level of variables, knowledge about probabilistic influences that hold only for specific values cannot be expressed. The results computed from a qualitative network, as a consequence, can be weaker than strictly necessary and may in fact be rather uninformative. We extend the basic formalism of qualitative probabilistic networks by providing for the inclusion of context-specific information about influences and show that exploiting this information upon reasoning has the ability to forestall unnecessarily weak results.