Uncertainty in Artificial Intelligence
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Representing Heuristic Knowledge in D-S Theory
Weiru Liu, John Hughes, Michael McTear
Abstract:
The Dempster-Shafer theory of evidence has been used intensively to deal with uncertainty in knowledge-based systems. However the representation of uncertain relationships between evidence and hypothesis groups (heuristic knowledge) is still a major research problem. This paper presents an approach to representing such heuristic knowledge by evidential mappings which are defined on the basis of mass functions. The relationships between evidential mappings and multi valued mappings, as well as between evidential mappings and Bayesian multi- valued causal link models in Bayesian theory are discussed. Following this the detailed procedures for constructing evidential mappings for any set of heuristic rules are introduced. Several situations of belief propagation are discussed.
Keywords:
Pages: 182-190
PS Link:
PDF Link: /papers/92/p182-liu.pdf
BibTex:
@INPROCEEDINGS{Liu92,
AUTHOR = "Weiru Liu and John Hughes and Michael McTear",
TITLE = "Representing Heuristic Knowledge in D-S Theory",
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 = "182--190"
}


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