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

2013/02/20 by Liem Viet Ngo, Ngo, Liem, Peter Haddawy +3
Computer Science · #Bayesian Modeling and Causal Inference #Logic, Reasoning, and Knowledge #Semantic Web and Ontologies

paper · pdf · doi:10.48550/arxiv.1302.4974

Abstract

We define a context-sensitive temporal probability logic for representing\nclasses of discrete-time temporal Bayesian networks. Context constraints allow\ninference to be focused on only the relevant portions of the probabilistic\nknowledge. We provide a declarative semantics for our language. We present a\nBayesian network construction algorithm whose generated networks give sound and\ncomplete answers to queries. We use related concepts in logic programming to\njustify our approach. We have implemented a Bayesian network construction\nalgorithm for a subset of the theory and demonstrate it's application to the\nproblem of evaluating the effectiveness of treatments for acute cardiac\nconditions.\n

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