Limits to Knowledge Level-B Modeling (and KADS)

TL;DRAbstract

Despite the current enthusiasm for knowledge level-B modeling in general and KADS in particular, we find there exists little empirical proof of the utility of this approach. In this paper, we will review the available evidence to suggest that alternative, less abstract, approaches may be better than KADS. 1 Introduction In the 1970s and early 1980s, several high-profile expert system successes were documented: e.g. MYCIN [49], CASNET [45], PROSPECTOR [6, 14], and XCON [2]. However, despite careful attempts to generalise this work (e.g. [42]), expert systems construction remained a somewhat hit-and-miss process. By the end of the 1980s, it was recognised that our design concepts for knowledge-based systems were incomplete [5]. A new expert system design approach (which has come to dominant the knowledge acquisition (KA) field) is the the search for reusable abstract domain-independent problem-solving strategies. We call this approach KLB since it is a variant of Newell's knowle

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