A fuzzy multipreference semantics has been recently proposed for weighted conditional knowledge bases, and used to develop a logical semantics for Multilayer Perceptrons, by regarding a deep neural network (after training) as a weighted conditional knowledge base. This semantics, in its different variants, suggests some gradual argumentation semantics, which are related to the family of the gradual semantics. The relationships between weighted conditional knowledge bases and MLPs extend to the proposed gradual semantics, which captures the stationary states of MPs, so that a dee neural network can as well be seen as a weighted argumentation graph.
翻译：最近为加权有条件知识基础提出了一个模糊的多选项语义学建议,并用于为多层受控者开发逻辑语义学,其方法是将深神经网络(培训后)视为加权有条件知识基础。 这种语义学在不同变量中暗示了一些渐进的语义学,这些语义学与渐进语义的组合有关。 加权有条件知识基础和 MLPs之间的关系延伸到了拟议的渐进语义学,它捕捉了MPs的固定状态,因此,dee 神经网络也可以被视为加权引论图表。
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