Intelligent Systems Engineering

More and more we hear the complaint that the gap between research and instruction is widening and a vital sense of motivation is falling between the cracks. It is our vision that intelligent computing systems will become a partner in the reintegration of discovery and learning within the inquiry process. We will address certain issues that must be faced if computer media are to have the characteristics necessary to support this integration. The development of the computer to date has required a careful attention to the syntax and semantics of the rather limited symbol systems we have induced them to use. A capacity for communicating in multiple modalities with non-uniform communities of symbol users — for sharing in the discovery of a pluralistic universe — will demand a quantum leap in our understanding of the pragmatic dimensions of symbol use. In the future the capacity for inquiry must permeate the living architecture of the computer system. A computer program that begins to embody these ideas will be discussed.

Model-based diagnosis is regarded by many as a way to overcome the limitations of first-generation knowledge-based systems which perform fault classification by means of empirical symptom-failure associations. Many different approaches to model-based diagnosis exist. The ESPRIT ARTIST project, focusing on the development of model-based techniques for diagnosis of industrial systems, has tried to integrate these approaches within a common generic architecture so that a given application system could be generated by composing a particular diagnostic system from a set of predeveloped and hence reusable modules. There is an overview of the main results of the ARTIST project, its generic architecture and the three diagnostic systems developed and tested within the project. An industrial application to management of electrical transmission networks is presented.