工业系统中知识表示与推理的edward - venn图

A. Dvoryanchikova, A. Lobov, A. Capanji, J. Lastra
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引用次数: 0

摘要

在工业系统建模的连接方法中,为了方便知识表示和推理,引入了爱德华-维恩图(EVD)。由于能够捕获对人类和机器都可解释的知识,语义描述被认为有助于解决大规模定制的挑战。然而,现代知识技术在表达工业系统所必需的事件和过程的动态性质的语义方面不能提供所需的灵活性。这激发了对知识表示和推理的灵活而正式的工具的进一步研究。为了对工业系统的动态质量提供灵活的语义描述,受自然认知的联结主义方法衍生的自然知识结构的启发,提出了一种联结主义知识模型——联结主义概念网格(connectionistic concept grid, CCG)。EVD可用于表示CCG中不同概念集之间的关系,并在模型中提供结构推理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Edwards-Venn Diagrams for knowledge representation and reasoning in industrial systems
Edwards-Venn Diagrams (EVD) were introduced to facilitate knowledge representation and reasoning in connectionistic approach for modeling industrial systems. Semantic descriptions are seen helpful in solving the challenges of mass customization due to capability to capture knowledge interpretable both for humans and machines. However modern knowledge technologies could not provide required flexibility in expressing the semantics of dynamical nature of events and processes which are essential for industrial systems. This motivates further research for flexible yet formal tools for knowledge representation and reasoning. In order to provide flexible semantic descriptions to dynamic qualities of industrial systems, a connectionistic knowledge model — connectionistic concept grid (CCG) — was introduced, which was inspired by natural knowledge structure derived from connectionism approach to natural cognition. EVD were found useful to represent relations among different sets of concepts in CCG and to provide structural reasoning in the models.
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