Fusion of knowledge-based systems and neural networks and applications

R. Khosla, T. Dillon
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引用次数: 5

Abstract

Neural Networks and Symbolic Knowledge-Based Systems each have their strengths and weaknesses. Intelligent Systems that fuse these two paradigms overcome a significant number of the weaknesses of each individual paradigm. There are many different approaches in the literature (including research from the author's own group) to fusing these paradigms. A critical evaluation of these approaches is given within the paper.
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基于知识的系统与神经网络及应用的融合
神经网络和符号知识系统各有优缺点。融合这两种范式的智能系统克服了每一种范式的大量弱点。文献中有许多不同的方法(包括作者自己小组的研究)来融合这些范式。本文对这些方法进行了批判性的评价。
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