Uncertainty in Artificial Intelligence
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Causes and Explanations: A Structural-Model Approach --- Part 1: Causes
Joseph Halpern, Judea Pearl
Abstract:
We propose a new definition of actual causes, using structural equations to model counterfactuals.We show that the definitions yield a plausible and elegant account ofcausation that handles well examples which have caused problems forother definitions and resolves major difficulties in the traditionalaccount. In a companion paper, we show how the definition of causality can beused to give an elegant definition of (causal) explanation.
Keywords:
Pages: 194-202
PS Link: http://www.cs.cornell.edu/home/halpern/papers/actcaus.ps
PDF Link: /papers/01/p194-halpern.pdf
BibTex:
@INPROCEEDINGS{Halpern01,
AUTHOR = "Joseph Halpern and Judea Pearl",
TITLE = "Causes and Explanations: A Structural-Model Approach --- Part 1: Causes",
BOOKTITLE = "Proceedings of the Seventeenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-01)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "2001",
PAGES = "194--202"
}


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