Uncertainty in Artificial Intelligence
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Causality in Bayesian Belief Networks
Marek Druzdzel, Herbert Simon
Abstract:
We address the problem of causal interpretation of the graphical structure of Bayesian belief networks (BBNs). We review the concept of causality explicated in the domain of structural equations models and show that it is applicable to BBNs. In this view, which we call mechanism-based, causality is defined within models and causal asymmetries arise when mechanisms are placed in the context of a system. We lay the link between structural equations models and BBNs models and formulate the conditions under which the latter can be given causal interpretation.
Keywords:
Pages: 3-11
PS Link:
PDF Link: /papers/93/p3-druzdzel.pdf
BibTex:
@INPROCEEDINGS{Druzdzel93,
AUTHOR = "Marek Druzdzel and Herbert Simon",
TITLE = "Causality in Bayesian Belief Networks",
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 = "3--11"
}


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