Abstract
Many artificial intelligence approaches to automated fault diagnosis employ functional or symptomatic abstraction hierarchies in their reasoning process. However, these approaches fail to provide rapid response and adaptability comparable to humans experts. This paper presents an approach which allows robust, unstructured switching between abstraction levels and types using agents that examine the problem domain from different perspectives. This approach was implemented and tested with promising results.
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Fries, T.P., Graham, J.H. (2000). An Agent-Based Approach to Robust Switching Between Abstraction Levels for Fault Diagnosis. In: Choueiry, B.Y., Walsh, T. (eds) Abstraction, Reformulation, and Approximation. SARA 2000. Lecture Notes in Computer Science(), vol 1864. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44914-0_20
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DOI: https://doi.org/10.1007/3-540-44914-0_20
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