Search Results

Documents authored by de Kleer, Johan

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)

Copy BibTex To Clipboard

@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)

Copy BibTex To Clipboard

@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)

Copy BibTex To Clipboard

@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}
}
Any Issues?
X

Feedback on the Current Page

CAPTCHA

Thanks for your feedback!

Feedback submitted to Dagstuhl Publishing

Could not send message

Please try again later or send an E-mail
© 2023-2025 Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact