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：本文研究了知识表示中可击败推理的多重偏好语义与多层神经网络模型之间的关系。在（多值）“概念层面”的多重偏好语义下，考虑了带典型性的简单描述逻辑的加权知识库。该语义被用于为多层感知机（MLPs）提供偏好解释。在验证MLPs的条件性质时，采用了模型检测与基于蕴涵的方法。