2026-09-28T11:51:14Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:27823 2026-09-28T06:35:13Z ddc:004 open_access

On the Practical Utility of Diagnoses Pill, Ingo de Kleer, Johan Model-based Diagnosis Diagnosis Algorithms Diagnoses address a universal need for explanations that arises whenever things go wrong or when we observe some unexpected behavior. The ubiquitous need for such explanations has led to an abundance of algorithmic concepts and computation variants for diagnostic processes. Comparisons have mainly focused on highlighting the virtues of individual algorithms or the required computational efforts. In this paper, we focus on evaluating the results of a diagnosis algorithm in the context of an inspection and repair process. We completely ignore the algorithm’s computation concept and whether the observations would justifiably support multiple diagnoses. In particular, we focus on inspecting and discussing the practical utility of diagnoses as a measure of the unnecessary efforts one has to spend when fully repairing a system. We start with assessing the utility of a single diagnosis and then progress to evaluating ambiguity groups, i.e., sets of diagnoses. We propose corresponding metrics that investigate worst case and average performance, contrast them to the utility metric used in the DX Competition 2010, and discuss the metrics' results for several scenarios. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Ingo Pill and Johan de Kleer 2026 Is Part Of OASIcs, Volume 148, 37th International Conference on Principles of Diagnosis and Resilient Systems (DX 2026) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.DX.2026.9 urn:nbn:de:0030-drops-278233 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.DX.2026.9 eng https://creativecommons.org/licenses/by/4.0/legalcode