Combining Case-based Reasoning and Task Speci c Architectures
نویسنده
چکیده
Certain weaknesses of Expert System technology became apparent in the early 80's. Among them were the `knowledge acquisition bottleneck' and problems of robustness. Among the proposals in the 1980s to resolve these problems are Case Based Reasoning (CBR) and Task Speci c Architectures (TSA). Case Based Reasoning resolves these problems by representing knowledge in cases cases are generalized when a new problem is seen, and the speci c requirements of the case are known. Task Speci c Architectures take advantage of commonalities among several expert system applications, to project these into the engineering of future systems. Case-based Reasoning recognizes the power of individual solutions, while task-speci c architectures take advantage of commonalities among solutions. Although these two approaches exploit di erent aspects of knowledge-based systems, integrating them into one system is not obvious. Case-based reasoning insists that knowledge be represented in cases, while TSAs represent knowledge in task structures. This paper presents two di erent ways to gain the advantages of both.
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