Uncertainty in Artificial Intelligence
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Exploiting Functional Dependencies in Qualitative Probabilistic Reasoning
Michael Wellman
Abstract:
Functional dependencies restrict the potential interactions among variables connected in a probabilistic network. This restriction can be exploited in qualitative probabilistic reasoning by introducing deterministic variables and modifying the inference rules to produce stronger conclusions in the presence of functional relations. I describe how to accomplish these modifications in qualitative probabilistic networks by exhibiting the update procedures for graphical transformations involving probabilistic and deterministic variables and combinations. A simple example demonstrates that the augmented scheme can reduce qualitative ambiguity that would arise without the special treatment of functional dependency. Analysis of qualitative synergy reveals that new higher-order relations are required to reason effectively about synergistic interactions among deterministic variables.
Keywords: null
Pages: 3-15
PS Link:
PDF Link: /papers/90/p3-wellman.pdf
BibTex:
@INPROCEEDINGS{Wellman90,
AUTHOR = "Michael Wellman ",
TITLE = "Exploiting Functional Dependencies in Qualitative Probabilistic Reasoning",
BOOKTITLE = "Uncertainty in Artificial Intelligence 6 Annual Conference on Uncertainty in Artificial Intelligence (UAI-90)",
PUBLISHER = "Elsevier Science",
ADDRESS = "Amsterdam, NL",
YEAR = "1990",
PAGES = "3--15"
}


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