In this paper, we extend the QMR-DT probabilistic model for the domain of internal medicine to include decisions about treatments. In addition, we describe how we can use the comp...
We examine the notion of "unrelatedness" in a probabilistic framework. Three formulations are presented. In the first formulation, two variables a and b are totally inde...
The intelligent reformulation or restructuring of a belief network can greatly increase the efficiency of inference. However, time expended for reformulation is not available for ...
In this paper, the feasibility of using finite totally ordered probability models under Aleliunas’s Theory of Probabilistic Logic [Aleliunas, 1988] is investigated. The general...
In learning belief networks, the single link lookahead search is widely adopted to reduce the search space. We show that there exists a class of probabilistic domain models which ...
The main goal of this paper is to describe a data structure called binary join trees that are useful in computing multiple marginals efficiently using the Shenoy-Shafer architectu...
We propose a decision-analytical approach to comparing the flexibility of decision situations from the perspective of a decisionmaker who exhibits constant risk-aversion over a mo...