Constructing Situation Specific Belief Networks
arXiv:1301.7399
Abstract
This paper describes a process for constructing situation-specific belief networks from a knowledge base of network fragments. A situation-specific network is a minimal query complete network constructed from a knowledge base in response to a query for the probability distribution on a set of target variables given evidence and context variables. We present definitions of query completeness and situation-specific networks. We describe conditions on the knowledge base that guarantee query completeness. The relationship of our work to earlier work on KBMC is also discussed.
Appears in Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI1998)
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