Working group in model-based design and reasoning. Part I: modeling and diagnosis
B Faltings - AI Communications, 1996 - journals.sagepub.com
AI Communications, 1996•journals.sagepub.com
Classical artificial intelligence techniques such as expert systems have often been found to
be too brittle for large-scale applications. Model-based reasoning is a technique for making
artificial intelligence software applicable to problems of realistic size. In this working group,
we have investigated some fundamental issues in model-based reasoning and various
applications in diagnosis, control and design. This paper reports on the results in basic
techniques as well as diagnosis applications obtained at EPFL, ETHZ, Landis & Gyr and …
be too brittle for large-scale applications. Model-based reasoning is a technique for making
artificial intelligence software applicable to problems of realistic size. In this working group,
we have investigated some fundamental issues in model-based reasoning and various
applications in diagnosis, control and design. This paper reports on the results in basic
techniques as well as diagnosis applications obtained at EPFL, ETHZ, Landis & Gyr and …
Classical artificial intelligence techniques such as expert systems have often been found to be too brittle for large-scale applications. Model-based reasoning is a technique for making artificial intelligence software applicable to problems of realistic size.
In this working group, we have investigated some fundamental issues in model-based reasoning and various applications in diagnosis, control and design. This paper reports on the results in basic techniques as well as diagnosis applications obtained at EPFL, ETHZ, Landis & Gyr and Nestlé. The results of the part dealing with design are reported in another paper in this issue, pp. 65–73.
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