Knowledge Engineering for Large Belief Networks

Reference: Pradhan, M.; Provan, G.; Middleton, B.; & Henrion, M. Knowledge Engineering for Large Belief Networks. Knowledge Systems Laboratory, Medical Computer Science, June, 1994.

Abstract: We present several techniques for knowledge engineering of large belief networks (BNs) based on the our experiences with a network derived from a large medical knowledge base. The noisy-max, a generalization of the noisy-or gate, is used to model causal independence in a bn with multi-valued variables. We describe the use of leak probabilities to enforce the closed-world assumption in our model. We present Netview, a visualization tool based on causal independence and the use of leak probabilities. The Netview software allows knowledge engineers to dynamically view subnetworks for knowledge engineering, and it provides version control for editing a BN. Netvew generates subnetworks in which leak probabilities are dynamically updated to reflect the missing portions of the network.

Full paper available as ps.

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