Constructing Situation Specific Belief Networks
Suzanne Mahoney, Kathryn Laskey
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.
PDF Link: /papers/98/p370-mahoney.pdf
AUTHOR = "Suzanne Mahoney
and Kathryn Laskey",
TITLE = "Constructing Situation Specific Belief Networks",
BOOKTITLE = "Proceedings of the Fourteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-98)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1998",
PAGES = "370--378"