Foundations of cognitive science : overview
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چکیده
kind, imposing constraints upon the possible organizations of intelligent systems rather than upon their material substrates. Intelligent systems, according to this argument, will necessarily be symbol systems, and at the level of goal-oriented activity, they will be serial in operation with, narrow attentional focus. Empirically Observed Invariants However adaptive are the intelligent systems with which we are concerned, we should not despair completely of finding invariants in their behavior. For example, the study of expertise in humans and research on the design of expert systems for computers have revealed some remarkable uniformities and generalizations. These uniformities stem from both the limitations imposed by inner environments and the task demands of the outer environments. Expertise, empirical research shows, generally rests on an extensive knowledge base. It has been shown for a number of fields of human endeavor that a worldclass level of expertise is never attained with less than ten years of concentrated learning and practice. Here, the magic number 10 represents a ratio between the amount of knowledge and skill that has to be acquired by the expert (the demand of the external environment) and the rate at which people can acquire knowledge and skill (the limits of the inner environment). With respect to the size of the knowledge base, it has been found that thousands or tens of thousands of productions must be provided to a sophisticated expert system like a medical diagnosis system. Research on human world-class experts has shown that their knowledge bases are likely to amount to 50,000 or 100,000 productions or more. Numbers of the same magnitude characterize typical natural-language vocabularies of professionals. The ubiquitous presence of large knowledge bases like these is a characteristic invariant of human and mechanical expert systems.
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تاریخ انتشار 2016