Uncertainty in Artificial Intelligence
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Representing Context-Sensitive Knowledge in a Network Formalism: A Preliminary Report
Tze-Yun Leong
Abstract:
Automated decision making is often complicated by the complexity of the knowledge involved. Much of this complexity arises from the context sensitive variations of the underlying phenomena. We propose a framework for representing descriptive, context-sensitive knowledge. Our approach attempts to integrate categorical and uncertain knowledge in a network formalism. This paper outlines the basic representation constructs, examines their expressiveness and efficiency, and discusses the potential applications of the framework.
Keywords:
Pages: 166-173
PS Link:
PDF Link: /papers/92/p166-leong.pdf
BibTex:
@INPROCEEDINGS{Leong92,
AUTHOR = "Tze-Yun Leong ",
TITLE = "Representing Context-Sensitive Knowledge in a Network Formalism: A Preliminary Report",
BOOKTITLE = "Proceedings of the Eighth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-92)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Mateo, CA",
YEAR = "1992",
PAGES = "166--173"
}


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