Jonathan Wurth

Wissenschaftlicher Mitarbeiter
Lehrstuhl für Organic Computing
Telefon: +49 821 598 69256
E-Mail:
Raum: 2044 (W)
Adresse: Am Technologiezentrum 8, 86159 Augsburg

Forschungsschwerpunkte

My primary research focus revolves around the automated design of metaheuristic algorithms (e.g., using hyper-heuristics). Metaheuristics are nature-inspired stochastic optimization methods that have proven to be highly effective in solving real-world problems where many exact methods are not applicable or fail to produce comparable results. Practitioners often encounter scenarios where they need to solve similar instances of optimization problems repeatedly, and metaheuristics specifically adapted to such instances have great potential over general search methods.

Automated metaheuristic design is an alternative to the complex and labor-intensive task of tailoring these algorithms by hand, and not only makes custom algorithms accessible to a much wider range of users, but also potentially outperforms human-designed algorithms by thoroughly exploring different design alternatives.
As part of my research, I am also interested in the following topics:

  • parameter control and tuning methodologies for metaheuristics
  • coevolutionary approaches
  • parallel and distributed algorithms
  • combining metaheuristics with machine learning
  • modular metaheuristic frameworks (e.g., using Rust)

 

Publikationen

2023 | 2022

2023

Helena Stegherr, Leopold Luley, Jonathan Wurth, Michael Heider and Jörg Hähner. 2023. A framework for modular construction and evaluation of metaheuristics.
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Michael Heider, Helena Stegherr, David Pätzel, Roman Sraj, Jonathan Wurth, Benedikt Volger and Jörg Hähner. 2023. Discovering rules for rule-based machine learning with the help of novelty search. DOI: 10.1007/s42979-023-02198-x
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Jonathan Wurth, Helena Stegherr, Michael Heider, Leopold Luley and Jörg Hähner. 2023. Fast, flexible, and fearless: a rust framework for the modular construction of metaheuristics. DOI: 10.1145/3583133.3596335
BibTeX | RIS | DOI

Michael Heider, Helena Stegherr, Roman Sraj, David Pätzel, Jonathan Wurth and Jörg Hähner. 2023. SupRB in the context of rule-based machine learning methods: a comparative study. DOI: 10.1016/j.asoc.2023.110706
BibTeX | RIS | DOI

2022

Michael Heider, Helena Stegherr, David Pätzel, Roman Sraj, Jonathan Wurth, Benedikt Volger and Jörg Hähner. 2022. Approaches for rule discovery in a learning classifier system. DOI: 10.5220/0011542000003332
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Jonathan Wurth, Michael Heider, Helena Stegherr, Roman Sraj and Jörg Hähner. 2022. Comparing different metaheuristics for model selection in a supervised learning classifier system. DOI: 10.1145/3520304.3529015
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Michael Heider, Helena Stegherr, Jonathan Wurth, Roman Sraj and Jörg Hähner. 2022. Investigating the impact of independent rule fitnesses in a learning classifier system. DOI: 10.1007/978-3-031-21094-5_11
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Michael Heider, Helena Stegherr, Jonathan Wurth, Roman Sraj and Jörg Hähner. 2022. Separating rule discovery and global solution composition in a learning classifier system. DOI: 10.1145/3520304.3529014
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Lebenslauf

seit 2023

Wissenschaftlicher Mitarbeiter am Lehrstuhl Organic Computing der Universität Augsburg

2021–2023 Wissenschaftliche Hilfskraft am Lehrstuhl Organic Computing der Universität Augsburg
2021–2023 Master-Studium im Fach Informatik an der Universität Augsburg
2018–2021 Bachelor-Studium im Fach Informatik an der Universität Augsburg

Lehrveranstaltungen

(Angewandte Filter: Semester: aktuelles | Institutionen: Organic Computing | Dozenten: Jonathan Wurth | Vorlesungsarten: alle)
Name Semester Typ
Studentische Arbeiten am Lehrstuhl Organic Computing Wintersemester 2023/24 sonstige
Seminar Organic Computing (Bachelor) Wintersemester 2023/24 Seminar
Seminar Organic Computing (Master) Wintersemester 2023/24 Seminar

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