In this paper we investigate the relationships between a multipreferential semantics for defeasible reasoning in knowledge representation and a multilayer neural network model. Weighted knowledge bases for a simple description logic with typicality are considered under a (many-valued) ``concept-wise" multipreference semantics. The semantics is used to provide a preferential interpretation of MultiLayer Perceptrons (MLPs). A model checking and an entailment based approach are exploited in the verification of conditional properties of MLPs.

翻译：本文探讨了知识表示中可废止推理的多重优先语义与多层神经网络模型之间的关系。我们考虑了基于典型性的简单描述逻辑的加权知识库，并采用（多值）"概念-wise"多重优先语义。该语义用于提供多层感知器（MLPs）的优先性解释。在验证MLP的条件性质时，我们利用了模型检测和蕴含推理两种方法。