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Different decision algorithms make different assumptions about the structure of a decision maker's anticipations about states and outcomes. A proper fit between the algorithm and the actual information available is needed for good decision support.
A method of fuzzy ordinal decision analysis is presented in which some outcomes are infinitely bad and some nonzero links are infinitesimally small: not well measurably different from zero. The method is illustrated in the context of community acceptance of a high containment biological research laboratory.
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