English

Constructing Situation Specific Belief Networks

Artificial Intelligence 2013-02-01 v1

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.

Keywords

Cite

@article{arxiv.1301.7399,
  title  = {Constructing Situation Specific Belief Networks},
  author = {Suzanne M. Mahoney and Kathryn Blackmond Laskey},
  journal= {arXiv preprint arXiv:1301.7399},
  year   = {2013}
}

Comments

Appears in Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI1998)

R2 v1 2026-06-21T23:18:08.642Z