Uncertainty in Artificial Intelligence
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Network Engineering for Complex Belief Networks
Suzanne Mahoney, Kathryn Laskey
Abstract:
Like any large system development effort, the construction of a complex belief network model requires systems engineering to manage the design and construction process. We propose a rapid prototyping approach to network engineering. We describe criteria for identifying network modules and the use of "stubs" to represent not-yet-constructed modules. We propose an object oriented representation for belief networks which captures the semantics of the problem in addition to conditional independencies and probabilities. Methods for evaluating complex belief network models are discussed. The ideas are illustrated with examples from a large belief network construction problem in the military intelligence domain.
Keywords: Knowledge engineering, Bayesian networks, spiral model, knowledge representation, ob
Pages: 389-396
PS Link: FTP://site.gmu.edu/people/klaskey/papers/neteng.ps
PDF Link: /papers/96/p389-mahoney.pdf
BibTex:
@INPROCEEDINGS{Mahoney96,
AUTHOR = "Suzanne Mahoney and Kathryn Laskey",
TITLE = "Network Engineering for Complex Belief Networks",
BOOKTITLE = "Proceedings of the Twelfth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-96)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1996",
PAGES = "389--396"
}


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