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Logic-motivated choice of fuzzy logic operators

机译:模糊逻辑运算符的逻辑驱动选择

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Many different "and"- and "or"-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 "and"- and "or"-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 "the most logical". 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.
机译:已经提出了许多不同的“与”和“或”运算用于模糊逻辑。因此,重要的是为每个特定应用选择最适合该特定应用的操作。当主要标准是获得最稳定的控制(或最平滑或最鲁棒或计算最快)时,有几篇论文讨论了模糊控制的“和”和“或”运算的最佳选择。然而,在推理应用中,选择最能反映人类推理的操作,即“最合乎逻辑”的操作更为合适。在本文中,我们解释了如何利用逻辑动机选择模糊逻辑运算,并说明了这种选择的后果。作为意外后果之一,我们与在不确定性概率方法中众所周知的熵技术得到了令人惊讶的关系。

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