Efficient sensor selection for active information fusion
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
Simultaneous decision networks with multiple objectives as support for strategic planning
MDAI'06 Proceedings of the Third international conference on Modeling Decisions for Artificial Intelligence
Multiagent decision by partial evaluation
Canadian AI'12 Proceedings of the 25th Canadian conference on Advances in Artificial Intelligence
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Evaluating an influence diagram (ID) is a challenging problem because its complexity increases exponentially in the number of decision nodes in the diagram. In this paper, we examine the problem for a special class of IDs where multiple decisions must be made simultaneously. We describe a brief theory that factorizes out the computations common to all policies in evaluating them. Our evaluation approach conducts these computations once and uses them across all policies. We identify the ID structures for which the approach can achieve savings. We show that the approach can be used to efficiently recompute the optimal policy of an ID when its structure or parameters change. Finally, we demonstrate the superior performance of the approach by simulation studies and a military planning example