Abstract
The goal of cognitive psychologists interested in human expertise is to identify the cognitive structures and processes that are responsible for skilled performance within a domain. It is assumed that these structures and processes maintain some degree of generality regardless of the specific content of knowledge (i.e., the specific facts and rules making up the knowledge base). On the other hand, the goal of those interested in expert systems is often quite different. For knowledge engineers, the development of the expert system is the goal, and the explanation of expertise is typically secondary at most. Also, because knowledge, in the form of specific facts and rules, is assumed to be the power behind expert systems (Minsky & Papert, 1974), knowledge engineers tend to be less concerned with general characteristics of expert knowledge than they are with the specific content of that knowledge. As a consequence, knowledge acquisition, the process of transferring knowledge from a source of expertise (either human or textual) to the expert system, is of paramount importance to the development of expert systems, but unfortunately it is also a major bottleneck in expert system design. Although the bulk of the research that has been done in cognitive psychology on expertise does not directly address the elicitation of specific facts and rules from human experts, methods that have been used in cognitive psychology to study memory organization and expertise can be applied to the knowledge elicitation problem. Furthermore, there are numerous arguments for considering the knowledge engineering implications of cognitive research related to the general structures and processes that underlie expertise.
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Cooke, N.J. (1992). Modeling Human Expertise in Expert Systems. In: Hoffman, R.R. (eds) The Psychology of Expertise. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-9733-5_3
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