Weighted knowledge bases for description logics with typicality have been recently considered under a "concept-wise" multipreference semantics (in both the two-valued and fuzzy case), as the basis of a logical semantics of MultiLayer Perceptrons (MLPs). In this paper we consider weighted conditional ALC knowledge bases with typicality in the finitely many-valued case, through three different semantic constructions. For the boolean fragment LC of ALC we exploit ASP and "asprin" for reasoning with the concept-wise multipreference entailment under a phi-coherent semantics, suitable to characterize the stationary states of MLPs. As a proof of concept, we experiment the proposed approach for checking properties of trained MLPs.

翻译：用于典型描述逻辑的加权知识基础最近已在“概念性”多偏差语义学(在两值和模糊的情况下)下被视为多光子逻辑语义学的基础。在本文中,我们通过三种不同的语义构造,将有限多光谱案例典型的加权有条件的ALC知识基础视为加权的有条件知识基础。对于ALC的布林碎片LC,我们利用ASP和“草皮”来进行与概念性多光谱语义学相关的推理,这适合于描述MLP的固定状态。作为概念的证明,我们试验了检查受过训练的MLP特性的拟议方法。