Uncertainty in Artificial Intelligence
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Incremental Probabilistic Inference
Bruce D'Ambrosio
Abstract:
Propositional representation services such as truth maintenance systems offer powerful support for incremental, interleaved, problem-model construction and evaluation. Probabilistic inference systems, in contrast, have lagged behind in supporting this incrementality typically demanded by problem solvers. The problem, we argue, is that the basic task of probabilistic inference is typically formulated at too large a grain-size. We show how a system built around a smaller grain-size inference task can have the desired incrementality and serve as the basis for a low-level (propositional) probabilistic representation service.
Keywords:
Pages: 301-308
PS Link:
PDF Link: /papers/93/p301-d_ambrosio.pdf
BibTex:
@INPROCEEDINGS{D'Ambrosio93,
AUTHOR = "Bruce D'Ambrosio ",
TITLE = "Incremental Probabilistic Inference",
BOOKTITLE = "Proceedings of the Ninth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-93)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1993",
PAGES = "301--308"
}


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