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Neural Networks and Structured Knowledge: Knowledge Representation and Reasoning

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Abstract

This collection of articles is the first of two parts of a special issue on “Neural Networks and Structured Knowledge.” The contributions to the first part shed some light on the issues of knowledge representation and reasoning with neural networks. Their scope ranges from formal models for mapping discrete structures like graphs or logical formulae onto different types of neural networks, to the construction of practical systems for various types of reasoning. In the second part to follow, the emphasis will be on the extraction of knowledge from neural networks, and on applications of neural networks and structured knowledge to practical tasks.

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  1. Department of Computer and Information Sciences, New Jersey Institute of Technology, Newark, NJ, 07102

    Franz J. Kurfess

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Kurfess, F.J. Neural Networks and Structured Knowledge: Knowledge Representation and Reasoning. Applied Intelligence 11, 5–13 (1999). https://doi.org/10.1023/A:1008327412259

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