Download PDFOpen PDF in browserInexpensive Cost-Optimized Measurement Proposal for Sequential Model-Based Diagnosis19 pages•Published: January 6, 2018AbstractIn this work we present strategies for (optimal) measurement computation and selection in model- based sequential diagnosis. In particular, assuming a set of leading diagnoses being given, we show how queries (sets of measurements) can be computed and optimized along two dimensions: expected number of queries and cost per query. By means of a suitable decoupling of two optimizations and a clever search space reduction the computations are done without any inference engine calls. For the full search space, we give a method requiring only a polynomial number of inferences and guarantee- ing query properties existing methods do not provide. Evaluation results using real-world problems indicate that the new method computes (virtually) optimal queries instantly independently of the size and complexity of the considered diagnosis problems.Keyphrases: measurement selection, query generation, sequential diagnosis In: Marina Zanella, Ingo Pill and Alessandro Cimatti (editors). 28th International Workshop on Principles of Diagnosis (DX'17), vol 4, pages 200-218.
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