Valuation Networks and Conditional Independence 191 Valuation Networks and Conditional Independence

pshenoy @ ukanvm.cc.ukans.edu Valuation networks have been proposed as graph-ical representations of valuation-based systems (VBSs). The VBS framework is able to capture many uncertainty calculi including probability theory, Dempster-Shafer’s belief-function theory, Spohn’s epistemic belief theory, and Zadeh’s possibility theory. In this paper, we show how valuation networks encode conditional indepen-dence relations. For the probabilistic case, the class of probability models encoded by valuation networks includes undirected graph models, di-rected acyclic graph models, directed balloon graph models, and recursive causal graph models.