Uncertainty in Artificial Intelligence
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Representation Requirements for Supporting Decision Model Formulation
Tze-Yun Leong
Abstract:
This paper outlines a methodology for analyzing the representational support for knowledge-based decision-modeling in a broad domain. A relevant set of inference patterns and knowledge types are identified. By comparing the analysis results to existing representations, some insights are gained into a design approach for integrating categorical and uncertain knowledge in a context sensitive manner.
Keywords:
Pages: 212-219
PS Link:
PDF Link: /papers/91/p212-leong.pdf
BibTex:
@INPROCEEDINGS{Leong91,
AUTHOR = "Tze-Yun Leong ",
TITLE = "Representation Requirements for Supporting Decision Model Formulation",
BOOKTITLE = "Proceedings of the Seventh Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-91)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Mateo, CA",
YEAR = "1991",
PAGES = "212--219"
}


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