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.
翻译:在本文中,我们调查了用于在知识表述中进行不可行的推理的多优先语义与深层神经网络模型之间的关系。描述逻辑的加权知识基础在“概念性”多优先语义下审议。语义进一步扩展到模糊的解释,并被用来为多层概念提供优先解释。