Abstract
Knowledge-based configuration is both a successful application domain for AI techniques and and an active research area. An open issue in many practical domains is that of reconfiguration, typically exhibited by legacy systems that are to be extended, upgraded or simply altered. Standard configuration techniques are not necessarily suited to this task. We discuss the use of a diagnosis approach to reconfiguration. We present the differing application and representation requirements, develop a representation that is suitable for expressing the information about the required and configurable functionalities from the diagnosis point of view, present an example and discuss our experiences.
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Stumptner, M., Wotawa, F. (1998). Model-Based Reconfiguration. In: Gero, J.S., Sudweeks, F. (eds) Artificial Intelligence in Design ’98. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-5121-4_3
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DOI: https://doi.org/10.1007/978-94-011-5121-4_3
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