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      Using Potential Influence Diagrams for Probabilistic Inference and Decision Making

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          Abstract

          The potential influence diagram is a generalization of the standard "conditional" influence diagram, a directed network representation for probabilistic inference and decision analysis [Ndilikilikesha, 1991]. It allows efficient inference calculations corresponding exactly to those on undirected graphs. In this paper, we explore the relationship between potential and conditional influence diagrams and provide insight into the properties of the potential influence diagram. In particular, we show how to convert a potential influence diagram into a conditional influence diagram, and how to view the potential influence diagram operations in terms of the conditional influence diagram.

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          Author and article information

          Journal
          2013-03-06
          1303.1500

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

          Custom metadata
          UAI-P-1993-PG-383-390
          Appears in Proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence (UAI1993)
          cs.AI
          auai

          Artificial intelligence

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