| Abstract: | Knowledge modeling perspectives on knowledge acquisition suggest that it is reasonable to analyze knowledge bases as collections of models. This article focuses on those parts of the knowledge base that model the practical reasoning processes of human experts, and asks what properties those models might be expected to have. It surveys the general notion of a model and its connotations in information systems science. It analyze the structure of practical reasoning as a control process with information flows involving essential uncertainty and adaptivity, where robustness is more significant than optimality. Systemic considerations suggest that models of the relevant knowledge will consist of a collection of isolated productions, many of which will be concerned with avoidance rather than goal achievement. the relations of such models to role-limiting methods, generic tasks, and deep knowledge are discussed. Finally, the implications of the knowledge modeling perspectives for developments in knowledge acquisition are discussed. © 1993 John Wiley & Sons, Inc. |
