As Influence diagrams become a popular representational tool for decision analysis, influence diagram evaluation attracts more and more research interests. In this article, we present a new, two--phase method for influence diagram evaluation. In our method, an influence diagram is first mapped into a decision graph and then the analysis is carried out by evaluating the decision graph. Our method is more efficient than Howard and Matheson's two--phase method because, among other reasons, the size of the decision graph generated by our method from an influence diagram can be much smaller than that by Howard and Matheson's method for the same influence diagram. Like those most recent algorithms reported in the literature, our method can also exploit independence relationship among variables of decision problems, and provides a clean interface between influence diagram evaluation and Bayesian net evaluation, thus, various well--established algorithms for Bayesian net evaluation can be used in influence diagram evaluation. In this sense, our method is as efficient as those algorithms. Furthermore, our method has a few unique merits. First, it can take advantage of asymmetric processing in influence diagram evaluation. Second, by using heuristic search techniques, it provides an explicit mechanism for making use of heuristic information that may be available in a domain--specific form. These additional merits make our method more efficient than the current algorithms in general. Finally, by using decision graphs as an intermediate representation, the value of perfect information can be computed in a more efficient way.
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