Probabilistic inference in influence diagrams

Authors:
Nevin Lianwen Zhang
Affiliations:
Department of Computer Science, Hong Kong University of Science & Technology
Venue:
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Year:
1998

Citing 6
Cited 10

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Abstract

This paper is about reducing influence diagram (ID) evaluation into Bayesian network (BN) inference problems. Such reduction is interesting because it enables one to readily use one's favorite BN inference algorithm to efficiently evaluate IDS. Two such reduction methods have been proposed previously (Cooper 1988, Shachter and Peot 1992). This paper proposes a new method. The BN inference problems induced by the mew method are much easier to solve than those induced by the two previous methods.