Uncertainty in Artificial Intelligence
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Probabilistic Evaluation of Sequential Plans from Causal Models with Hidden Variables
Judea Pearl, James Robins
Abstract:
The paper concerns the probabilistic evaluation of plans in the presence of unmeasured variables, each plan consisting of several concurrent or sequential actions. We establish a graphical criterion for recognizing when the effects of a given plan can be predicted from passive observations on measured variables only. When the criterion is satisfied, a closed-form expression is provided for the probability that the plan will achieve a specified goal.
Keywords: Plan evaluation, causal effect, sequential treatments, causal diagrams, graphical mo
Pages: 444-453
PS Link:
PDF Link: /papers/95/p444-pearl.pdf
BibTex:
@INPROCEEDINGS{Pearl95,
AUTHOR = "Judea Pearl and James Robins",
TITLE = "Probabilistic Evaluation of Sequential Plans from Causal Models with Hidden Variables",
BOOKTITLE = "Proceedings of the Eleventh Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-95)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1995",
PAGES = "444--453"
}


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