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arXiv · 1302.4974

A Theoretical Framework for Context-Sensitive Temporal Probability Model Construction with Application to Plan Projection

Liem Ngo·Peter Haddawy·James Helwig
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Abstract

We define a context-sensitive temporal probability logic for representing classes of discrete-time temporal Bayesian networks. Context constraints allow inference to be focused on only the relevant portions of the probabilistic knowledge. We provide a declarative semantics for our language. We present a Bayesian network construction algorithm whose generated networks give sound and complete answers to queries. We use related concepts in logic programming to justify our approach. We have implemented a Bayesian network construction algorithm for a subset of the theory and demonstrate it's application to the problem of evaluating the effectiveness of treatments for acute cardiac conditions.

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Liem Ngo, Peter Haddawy, James Helwig. 2013-02-20. A Theoretical Framework for Context-Sensitive Temporal Probability Model Construction with Application to Plan Projection. https://arxiv.org/abs/1302.4974

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