  In this paper we investigate the relationships between a multipreferential
semantics for defeasible reasoning in knowledge representation and a deep
neural network model. Weighted knowledge bases for description logics are
considered under a "concept-wise" multipreference semantics. The semantics is
further extended to fuzzy interpretations and exploited to provide a
preferential interpretation of Multilayer Perceptrons.
