The role of assumptions in knowledge engineering

Problem‐solving methods are means of describing the inference process of knowledge‐based systems. In recent years, a number of these problem‐solving methods have been identified that can be reused for building new systems. However, problem‐solving methods require specific types of domain knowledge and introduce specific restrictions on the tasks that can be solved by them. These requirements and restrictions are assumptions that play a key role in the reuse of problem‐solving methods, in the acquisition of domain knowledge, and in the definition of the problem that can be tackled by knowledge‐based systems. In this paper we discuss the different roles assumptions play in the development of knowledge‐based systems and provide a survey of assumptions used in diagnostic problem solving. We show how such assumptions introduce targets and bias for goal‐driven machine learning and knowledge discovery techniques. © 1998 John Wiley & Sons, Inc.

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