论文标题
在有限多名的有条件知识库的有限多数语义下，在神经网络上推理的ASP方法
An ASP approach for reasoning on neural networks under a finitely many-valued semantics for weighted conditional knowledge bases
论文作者
论文摘要
最近在“概念”的多重语义（在两个值和模糊的情况下）中考虑了具有典型性的描述逻辑的加权知识库，这是多层感知器（MLP）逻辑语义的基础。在本文中，我们考虑了通过三种不同的语义构造在有限多名的情况下，在有限的多个估算情况下具有典型的加权条件ALC知识库。对于ALC的布尔片段LC，我们利用ASP和“ ASPRIN”来推理概念的多重率在Phi-coherent语义下，适合表征MLP的固定状态。作为概念证明，我们试验了拟议的方法来检查训练有素的MLP的特性。 该论文正在考虑在TPLP中接受。
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. The paper is under consideration for acceptance in TPLP.
