Abstract
This survey examines the roots of knowledge-based systems in artificial intelligence research, tracing them to the early realization that vast amounts of knowledge are a key to expert-level performance in AI systems. It considers both rule-based and frame-based implementation methods and their use in tools to ease the task of system construction. The survey concludes with an assessment of the current state of the art and with suggestions for some research directions that will be critical to providing improved methods for building knowledge-based systems.
Cite
CITATION STYLE
Szolovits, P. (1986). Knowledge-Based Systems: A Survey (pp. 339–352). https://doi.org/10.1007/978-1-4612-4980-1_28
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