Uncertainty in Artificial Intelligence
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A Study of Associative Evidential Reasoning
Yizong Cheng, Rangasami Kashyap
Abstract:
Evidential reasoning is cast as the problem of simplifying the evidence-hypothesis relation and constructing combination formulas that possess certain testable properties. Important classes of evidence as identifiers, annihilators, and idempotents and their roles in determining binary operations on intervals of reals are discussed. The appropriate way of constructing formulas for combining evidence and their limitations, for instance, in robustness, are presented.
Keywords:
Pages: 262-269
PS Link:
PDF Link: /papers/87/p262-cheng.pdf
BibTex:
@INPROCEEDINGS{Cheng87,
AUTHOR = "Yizong Cheng and Rangasami Kashyap",
TITLE = "A Study of Associative Evidential Reasoning",
BOOKTITLE = "Proceedings of the Third Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-87)",
PUBLISHER = "AUAI Press",
ADDRESS = "Corvallis, Oregon",
YEAR = "1987",
PAGES = "262--269"
}


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