Abstract
Imprecise information regarding feature values of an unidentified object is obtained from information sources of varying reliability. This imprecise information is used to construct a fuzzy probability distribution over the set of environments, which consist of all possible combinations of feature values. A fuzzy payoff matrix is constructed in which the rows represent all possible objects and the columns represent all possible environments. A fuzzy expected payoff is computed for each object (i.e., row) in this matrix. Each fuzzy expected payoff is then intersected with a maximizing set, and the object is identified as the one for which this intersection has the highest percentage of optimal values according to a specific criterion.
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