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Documents authored by de Kleer, Johan

Document
DOI: 10.4230/OASIcs.DX.2026.9
On the Practical Utility of Diagnoses

Authors: Ingo Pill and Johan de Kleer

Published in: OASIcs, Volume 148, 37th International Conference on Principles of Diagnosis and Resilient Systems (DX 2026)

Abstract
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.
Cite as

Ingo Pill and Johan de Kleer. On the Practical Utility of Diagnoses. In 37th International Conference on Principles of Diagnosis and Resilient Systems (DX 2026). Open Access Series in Informatics (OASIcs), Volume 148, pp. 9:1-9:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{pill_et_al:OASIcs.DX.2026.9,
  author =	{Pill, Ingo and de Kleer, Johan},
  title =	{{On the Practical Utility of Diagnoses}},
  booktitle =	{37th International Conference on Principles of Diagnosis and Resilient Systems (DX 2026)},
  pages =	{9:1--9:20},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-455-0},
  ISSN =	{2190-6807},
  year =	{2026},
  volume =	{148},
  editor =	{Pill, Ingo and Zanella, Marina and Provan, Gregory},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.DX.2026.9},
  URN =		{urn:nbn:de:0030-drops-278233},
  doi =		{10.4230/OASIcs.DX.2026.9},
  annote =	{Keywords: Model-based Diagnosis, Diagnosis, Algorithms}
}
Document
DOI: 10.4230/OASIcs.DX.2025.5
Assessing Diagnosis Algorithms: Of Sampling, Baselines, Metrics and Oracles

Authors: Ingo Pill and Johan de Kleer

Published in: OASIcs, Volume 136, 36th International Conference on Principles of Diagnosis and Resilient Systems (DX 2025)

Abstract
Assessing and comparing diagnosis algorithms is a surprisingly complex challenge. We have to make decisions ranging from identifying the implications of the chosen baseline, via defining and ensuring a representative sampling strategy, to the choice of metric best suited to capture the computational, probing, or repair costs as well as the deviations from the baseline. We discuss several aspects of the overall challenge, identify related issues, and evaluate a special economic metric.
Cite as

Ingo Pill and Johan de Kleer. Assessing Diagnosis Algorithms: Of Sampling, Baselines, Metrics and Oracles. In 36th International Conference on Principles of Diagnosis and Resilient Systems (DX 2025). Open Access Series in Informatics (OASIcs), Volume 136, pp. 5:1-5:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{pill_et_al:OASIcs.DX.2025.5,
  author =	{Pill, Ingo and de Kleer, Johan},
  title =	{{Assessing Diagnosis Algorithms: Of Sampling, Baselines, Metrics and Oracles}},
  booktitle =	{36th International Conference on Principles of Diagnosis and Resilient Systems (DX 2025)},
  pages =	{5:1--5:19},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-394-2},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{136},
  editor =	{Quinones-Grueiro, Marcos and Biswas, Gautam and Pill, Ingo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.DX.2025.5},
  URN =		{urn:nbn:de:0030-drops-247941},
  doi =		{10.4230/OASIcs.DX.2025.5},
  annote =	{Keywords: Model-based Diagnosis, Diagnosis, Algorithms}
}
Document
DX Competition
DOI: 10.4230/OASIcs.DX.2025.14
The DX Competition 2025 and Its Benchmarks (DX Competition)

Authors: Ingo Pill, Daniel Jung, Eldin Kurudzija, Anna Sztyber-Betley, Michał Syfert, Kai Dresia, Günther Waxenegger-Wilfing, and Johan de Kleer

Published in: OASIcs, Volume 136, 36th International Conference on Principles of Diagnosis and Resilient Systems (DX 2025)

Abstract
Fault diagnosis has been addressed in many research communities, leading to a variety of available fault diagnosis techniques. Deciding as a user which fault diagnosis methods are suitable for a specific application is thus a nontrivial task. Benchmarks can provide the community with a holistic understanding of the landscape of newly developed and available fault diagnosis methods when making this decision. After a long hiatus, we revived the DX Competition with three fault diagnosis benchmarks: SLIDe, LUMEN, and LiU-ICE. The purpose of the benchmarks is to inspire fault diagnosis research with challenging problems in cyber-physical systems relevant for industry. The benchmarks share a common code structure and we used similar performance metrics in order to simplify the adaptation of diagnosis system solutions to the different case studies.
Cite as

Ingo Pill, Daniel Jung, Eldin Kurudzija, Anna Sztyber-Betley, Michał Syfert, Kai Dresia, Günther Waxenegger-Wilfing, and Johan de Kleer. The DX Competition 2025 and Its Benchmarks (DX Competition). In 36th International Conference on Principles of Diagnosis and Resilient Systems (DX 2025). Open Access Series in Informatics (OASIcs), Volume 136, pp. 14:1-14:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{pill_et_al:OASIcs.DX.2025.14,
  author =	{Pill, Ingo and Jung, Daniel and Kurudzija, Eldin and Sztyber-Betley, Anna and Syfert, Micha{\l} and Dresia, Kai and Waxenegger-Wilfing, G\"{u}nther and de Kleer, Johan},
  title =	{{The DX Competition 2025 and Its Benchmarks}},
  booktitle =	{36th International Conference on Principles of Diagnosis and Resilient Systems (DX 2025)},
  pages =	{14:1--14:19},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-394-2},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{136},
  editor =	{Quinones-Grueiro, Marcos and Biswas, Gautam and Pill, Ingo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.DX.2025.14},
  URN =		{urn:nbn:de:0030-drops-248030},
  doi =		{10.4230/OASIcs.DX.2025.14},
  annote =	{Keywords: Diagnosis, Algorithms, Evaluation}
}
Document
DOI: 10.4230/OASIcs.DX.2024.6
Challenges for Model-Based Diagnosis

Authors: Ingo Pill and Johan de Kleer

Published in: OASIcs, Volume 125, 35th International Conference on Principles of Diagnosis and Resilient Systems (DX 2024)

Abstract
Since the seminal works by Reiter and de Kleer and Williams published in the late 80’s, Model-based Diagnosis has been a significant area of research. This has been motivated by the fact that MBD assists us in tackling a challenge that we face almost on a daily basis, i.e., by MBD allowing us to reason in a structured manner about the root causes for some encountered problem. MBD achieves this in an intuitive, complete and sound way, based on the central idea of investigating the compliance of some observed behavior with a model that describes how a system should behave - given this or that input scenario and parameter set. Over the last 40 years, MBD has been adopted for a multitude of applications, and we saw the emergence of a diverse set of algorithmic, optimizations, as well as extensions to the initial theoretical concepts.We argue that MBD remains highly relevant, with numerous scientific challenges to tackle as we face increasingly complex diagnostic problems. We discuss several such challenges and suggest related topics for PhD theses that have the potential to significantly contribute to the state-of-the-art in MBD research.
Cite as

Ingo Pill and Johan de Kleer. Challenges for Model-Based Diagnosis. In 35th International Conference on Principles of Diagnosis and Resilient Systems (DX 2024). Open Access Series in Informatics (OASIcs), Volume 125, pp. 6:1-6:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{pill_et_al:OASIcs.DX.2024.6,
  author =	{Pill, Ingo and de Kleer, Johan},
  title =	{{Challenges for Model-Based Diagnosis}},
  booktitle =	{35th International Conference on Principles of Diagnosis and Resilient Systems (DX 2024)},
  pages =	{6:1--6:20},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-356-0},
  ISSN =	{2190-6807},
  year =	{2024},
  volume =	{125},
  editor =	{Pill, Ingo and Natan, Avraham and Wotawa, Franz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.DX.2024.6},
  URN =		{urn:nbn:de:0030-drops-220983},
  doi =		{10.4230/OASIcs.DX.2024.6},
  annote =	{Keywords: Model-based Diagnosis, Diagnosis, Algorithms}
}

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