Hierarchical model-based diagnosis based on structural abstraction

摘要: Abstraction has been advocated as one of the main remedies for computational complexity model-based diagnosis. However, after seminal work published in early nineties, little research devoted to this topic. In paper, we consider types abstraction commonly used diagnosis, i.e., structural abstraction, investigating it both from a theoretical and practical point view. First, provide new formalization that generalizes extends previous ones. Then, present two different techniques diagnosis automatically derive easier-to-diagnose versions (hierarchical) problem on basis available observations. The proposed are formulated extensions well-known Mozetic's algorithm [I. Mozetic, Hierarchical in: W.H.L. Console, J. de Kleer (Eds.), Readings Model-Based Diagnosis, Morgan Kaufmann, San Mateo, CA, 1992, pp. 354-372], experimentally contrasted with evaluate obtained efficiency gains.