A New Method For Influence Diagram Evaluation

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 because, among other reasons, our method generates a much smaller decision graph for the same influence diagram. Like those most recent algorithms reported in the literature, our method also provides a clean interface between influence diagram evaluation and Bayesian net evaluation. Consequently, various well--established algorithms for Bayesian net evaluation can be used in influence diagram evaluation. Furthermore, our method has a few unique merits. First, it takes advantage of asymmetry in influence diagrams to avoid unnecessary computation. 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