From Weighted Conditionals of Multilayer Perceptrons to a Gradual Argumentation Semantics
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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.
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