Valuation-Based Systems for Bayesian Decision Analysis

Prakash P. Shenoy
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Prakash P. Shenoy: The University of Kansas, Lawrence, Kansas

Operations Research, 1992, vol. 40, issue 3, 463-484

Abstract: This paper proposes a new method for representing and solving Bayesian decision problems. The representation is called a valuation-based system and has some similarities to influence diagrams. However, unlike influence diagrams which emphasize conditional independence among random variables, valuation-based systems emphasize factorizations of joint probability distributions. Also, whereas influence diagram representation allows only conditional probabilities, valuation-based system representation allows all probabilities. The solution method is a hybrid of local computational methods for the computation of marginals of joint probability distributions and the local computational methods for discrete optimization problems. We briefly compare our representation and solution methods to those of influence diagrams.

Keywords: decision analysis; theory: representation; and solution using local computation; dynamic programming; Markov; finite state solution using local computation; networks/graphs: representation for decision; optimization and probabilistic inference problems (search for similar items in EconPapers)
Date: 1992
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Citations: View citations in EconPapers (18)

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