4 Search Results for "Langdon, William"

Document
DOI: 10.4230/OASIcs.DX.2025.7
One-Shot Learning in Hybrid System Identification: A New Modular Paradigm

Authors: Swantje Plambeck, Maximilian Schmidt, Louise Travé-Massuyès, and Goerschwin Fey

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

Abstract
Identification of hybrid systems requires learning models that capture both discrete transitions and continuous dynamics from observational data. Traditional approaches follow a stepwise process, separating trace segmentation and mode-specific regression, which often leads to inconsistencies due to unmodeled interdependencies. In this paper, we propose a new iterative learning paradigm that jointly optimizes segmentation and flow function identification. The method incrementally constructs a hybrid model by evaluating and expanding candidate flow functions over observed traces, introducing new modes only when existing ones fail to explain the data. The approach is modular and agnostic to the choice of the regression technique, allowing the identification of hybrid systems with varying levels of complexity. Empirical results on benchmark examples demonstrate that the proposed method produces more compact models compared to traditional techniques, while supporting flexible integration of different regression methods. By favoring fewer, more generalizable modes, the resulting models are not only likely to reduce complexity but also simplify diagnostic reasoning, improve fault isolation, and enhance robustness by avoiding overfitting to spurious mode changes.
Cite as

Swantje Plambeck, Maximilian Schmidt, Louise Travé-Massuyès, and Goerschwin Fey. One-Shot Learning in Hybrid System Identification: A New Modular Paradigm. In 36th International Conference on Principles of Diagnosis and Resilient Systems (DX 2025). Open Access Series in Informatics (OASIcs), Volume 136, pp. 7:1-7:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{plambeck_et_al:OASIcs.DX.2025.7,
  author =	{Plambeck, Swantje and Schmidt, Maximilian and Trav\'{e}-Massuy\`{e}s, Louise and Fey, Goerschwin},
  title =	{{One-Shot Learning in Hybrid System Identification: A New Modular Paradigm}},
  booktitle =	{36th International Conference on Principles of Diagnosis and Resilient Systems (DX 2025)},
  pages =	{7:1--7:18},
  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.2025.7},
  URN =		{urn:nbn:de:0030-drops-247969},
  doi =		{10.4230/OASIcs.DX.2025.7},
  annote =	{Keywords: Hybrid System, Model Learning, Symbolic Regression}
}
Document
DOI: 10.4230/DagRep.8.1.158
Genetic Improvement of Software (Dagstuhl Seminar 18052)

Authors: Justyna Petke, Claire Le Goues, Stephanie Forrest, and William B. Langdon

Published in: Dagstuhl Reports, Volume 8, Issue 1 (2018)

Abstract
We document the program and the immediate outcomes of Dagstuhl Seminar 18052 "Genetic Improvement of Software". The seminar brought together researchers in Genetic Improvement (GI) and related areas of software engineering to investigate what is achievable with current technology and the current impediments to progress and how GI can affect the software development process. Several talks covered the state-of-the-art and work in progress. Seven emergent topics have been identified ranging from the nature of the GI search space through benchmarking and practical applications. The seminar has already resulted in multiple research paper publications. Four by participants of the seminar will be presented at the GI workshop co-located with the top conference in software engineering - ICSE. Several researchers started new collaborations, results of which we hope to see in the near future.
Cite as

Justyna Petke, Claire Le Goues, Stephanie Forrest, and William B. Langdon. Genetic Improvement of Software (Dagstuhl Seminar 18052). In Dagstuhl Reports, Volume 8, Issue 1, pp. 158-182, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

Copy BibTex To Clipboard

@Article{petke_et_al:DagRep.8.1.158,
  author =	{Petke, Justyna and Le Goues, Claire and Forrest, Stephanie and Langdon, William B.},
  title =	{{Genetic Improvement of Software (Dagstuhl Seminar 18052)}},
  pages =	{158--182},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2018},
  volume =	{8},
  number =	{1},
  editor =	{Petke, Justyna and Le Goues, Claire and Forrest, Stephanie and Langdon, William B.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.8.1.158},
  URN =		{urn:nbn:de:0030-drops-92878},
  doi =		{10.4230/DagRep.8.1.158},
  annote =	{Keywords: genetic improvement GI, search-based software engineering SBSE, software optimisation, evolutionary improvement, automated software improvement, automated program repair, evolutionary computation, genetic programming, GP}
}
Document
DOI: 10.4230/DagSemProc.10361.2
2-bit Flip Mutation Elementary Fitness Landscapes

Authors: William Langdon

Published in: Dagstuhl Seminar Proceedings, Volume 10361, Theory of Evolutionary Algorithms (2010)

Abstract
Genetic Programming parity is not elementary. GP parity cannot be represented as the sum of a small number of elementary landscapes. Statistics, including fitness distance correlation, of Parity's fitness landscape are calculated. Using Walsh analysis the eigen values and eigenvectors of the Laplacian of the two bit flip fitness landscape are given and a ruggedness measure for elementary landscapes is proposed. An elementary needle in a haystack (NIH) landscape is given.
Cite as

William Langdon. 2-bit Flip Mutation Elementary Fitness Landscapes. In Theory of Evolutionary Algorithms. Dagstuhl Seminar Proceedings, Volume 10361, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)

Copy BibTex To Clipboard

@InProceedings{langdon:DagSemProc.10361.2,
  author =	{Langdon, William},
  title =	{{2-bit Flip Mutation Elementary Fitness Landscapes}},
  booktitle =	{Theory of Evolutionary Algorithms},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10361},
  editor =	{Anne Auger and Jonathan L. Shapiro and L. Darrell Whitley and Carsten Witt},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.10361.2},
  URN =		{urn:nbn:de:0030-drops-28146},
  doi =		{10.4230/DagSemProc.10361.2},
  annote =	{Keywords: Genetic Algorithms, Genetic Programming, search, optimisation, graph theory, Laplacian, Hamming cube}
}
Document
DOI: 10.4230/DagSemProc.06061.7
On Turing complete T7 and MISC F--4 program fitnes landscapes

Authors: William B. Langdon and Riccardo Poli

Published in: Dagstuhl Seminar Proceedings, Volume 6061, Theory of Evolutionary Algorithms (2006)

Abstract
We use the minimal instruction set F-4 computer to define a minimal Turing complete T7 computer suitable for genetic programming (GP) and amenable to theoretical analysis. Experimental runs and mathematical analysis of the T7, show the fraction of halting programs is drops to zero as bigger programs are run.
Cite as

William B. Langdon and Riccardo Poli. On Turing complete T7 and MISC F--4 program fitnes landscapes. In Theory of Evolutionary Algorithms. Dagstuhl Seminar Proceedings, Volume 6061, pp. 1-28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)

Copy BibTex To Clipboard

@InProceedings{langdon_et_al:DagSemProc.06061.7,
  author =	{Langdon, William B. and Poli, Riccardo},
  title =	{{On Turing complete T7 and MISC F--4 program fitnes landscapes}},
  booktitle =	{Theory of Evolutionary Algorithms},
  pages =	{1--28},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{6061},
  editor =	{Dirk V. Arnold and Thomas Jansen and Michael D. Vose and Jonathan E. Rowe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.06061.7},
  URN =		{urn:nbn:de:0030-drops-5956},
  doi =		{10.4230/DagSemProc.06061.7},
  annote =	{Keywords: Genetic programming}
}
  • Refine by Type
  • 4 Document/PDF
  • 1 Document/HTML

  • Refine by Publication Year
  • 1 2025
  • 1 2018
  • 1 2010
  • 1 2006

  • Refine by Author
  • 2 Langdon, William B.
  • 1 Fey, Goerschwin
  • 1 Forrest, Stephanie
  • 1 Langdon, William
  • 1 Le Goues, Claire
  • Show More...

  • Refine by Series/Journal
  • 1 OASIcs
  • 1 DagRep
  • 2 DagSemProc

  • Refine by Classification
  • 1 Computer systems organization → Embedded and cyber-physical systems
  • 1 Computing methodologies → Learning paradigms
  • 1 Computing methodologies → Modeling methodologies
  • 1 Computing methodologies → Symbolic and algebraic algorithms

  • Refine by Keyword
  • 1 GP
  • 1 Genetic Algorithms
  • 1 Genetic Programming
  • 1 Genetic programming
  • 1 Hamming cube
  • Show More...

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
© 2023-2026 Schloss Dagstuhl – LZI GmbH Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact