Probabilistic Evaluation of Sequential Plans from Causal Models with Hidden Variables
arXiv (Cornell University)Published 20 February 2013Open access
Judea Pearl, James M. Robins
Citations138
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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.
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Computer ScienceMathematics
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