Many different u22andu22- and u22oru22-operations have been proposed for use in fuzzy logic; it is therefore important to select, for each particular application, the operations which are the best for this particular application. Several papers discuss the optimal choice of u22andu22- and u22oru22-operations for fuzzy control, when the main criterion is to get the stablest control (or the smoothest or the most robust or the fastest-to-compute). In reasoning applications, however, it is more appropriate to select operations which are the best in reflecting human reasoning, i.e., operations which are u22the most logicalu22. In this paper, we explain how we can use logic motivations to select fuzzy logic operations, and show the consequences of this choice. As one of the unexpected consequences, we get a surprising relation with the entropy techniques, well known in probabilistic approach to uncertainty.
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