Practical Modeling of Bayesian Decision Problems -- Exploiting Deterministic Relations

Anders L. Madsen, Hugin Expert A/S, Denmark; Kristian G. Olesen, Aalborg University, Denmark; Søren L. Dittmer, Systematic Software Engineering, Denmark

The widespread use of influence diagrams to represent and solve Bayesian decision problems is still limited by the inflexibility and rather restrictive semantics of influence diagrams. In this paper, we propose a number of extensions and adjustments to the definition of influence diagrams in order to make the practical use of influence diagrams more flexible and less restrictive. In particular, we describe how deterministic relations can be exploited to increase the flexibility and efficiency of representing and solving Bayesian decision problems. The issues addressed in this paper were motivated by the construction of a decision support system for mission management of unmanned underwater vehicles.

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