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Knowledge Representation for Expert Systems: A Survey and Evaluation of Techniques
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English
Abstract
Knowledge representation plays a key role in the development of any Artificial Intelligence based system. A good representation can significantly shorten development time and execution speed, while a poor representation can doom a project.
Four representation techniques are commonly used to model knowledge in expert systems: logic, production rules, semantic networks, and frames. This paper describes the application of each of these techniques in modelling mechanical systems. Advantages and disadvantages for each of these techniques are presented.
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Citation
Dankel, D., "Knowledge Representation for Expert Systems: A Survey and Evaluation of Techniques," SAE Technical Paper 870110, 1987, https://doi.org/10.4271/870110.Also In
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