拉斯维加斯赌城

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Research foci

My research is focussed on nature-inspired optimisation algorithms, also known as metaheuristics or evolutionary algorithms. A main part of my work is the analysis of algorithmic behaviour, especially in relation to the components causing or influencing it. This is why I examine this topic from a conceptual perspective, highlighting similarities and differences of the optimisation algorithms, as well as from an empirical perspective, performing experiments to quantify the influence of different components on the overall algorthmic behaviour.

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In addition, I am interested in possibilities of combining metaheuristics and machine learning techniques, parallel and distributed algorithms, and methods and tools for experimental and statistical analyses of optimisation algorithms. I am also interested in applying metaheuristics to optimisation problems, especially from the field of bioinformatics.

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Publications

2024 | 2023 | 2022 | 2021 | 2020 | 2019

2024

Jonathan Wurth, Helena Stegherr, Michael Heider and J?rg H?hner. 2024. GRAHF: a hyper-heuristic framework for evolving heterogeneous island model topologies. DOI: 10.1145/3638529.3654136
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2023

Helena Stegherr, Leopold Luley, Jonathan Wurth, Michael Heider and J?rg H?hner. 2023. A framework for modular construction and evaluation of metaheuristics.
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Michael Heider, David P?tzel, Helena Stegherr and J?rg H?hner. 2023. A metaheuristic perspective on learning classifier systems. DOI: 10.1007/978-981-19-3888-7_3
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Michael Heider, Helena Stegherr, Richard Nordsieck and J?rg H?hner. 2023. Assessing model requirements for explainable AI: a template and exemplary case study. DOI: 10.1162/artl_a_00414
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Helena Stegherr, Michael Heider and J?rg H?hner. 2023. Assisting convergence behaviour characterisation with unsupervised clustering. DOI: 10.5220/0012202100003595
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Michael Heider, Helena Stegherr, David P?tzel, Roman Sraj, Jonathan Wurth, Benedikt Volger and J?rg H?hner. 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 J?rg H?hner. 2023. Fast, flexible, and fearless: a rust framework for the modular construction of metaheuristics. DOI: 10.1145/3583133.3596335
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Michael Heider, Helena Stegherr, Roman Sraj, David P?tzel, Jonathan Wurth and J?rg H?hner. 2023. SupRB in the context of rule-based machine learning methods: a comparative study. DOI: 10.1016/j.asoc.2023.110706
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2022

Michael Heider, Helena Stegherr, David P?tzel, Roman Sraj, Jonathan Wurth, Benedikt Volger and J?rg H?hner. 2022. Approaches for rule discovery in a learning classifier system. DOI: 10.5220/0011542000003332
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Helena Stegherr, Michael Heider and J?rg H?hner. 2022. Classifying metaheuristics: towards a unified multi-level classification system. DOI: 10.1007/s11047-020-09824-0
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Jonathan Wurth, Michael Heider, Helena Stegherr, Roman Sraj and J?rg H?hner. 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 J?rg H?hner. 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 J?rg H?hner. 2022. Separating rule discovery and global solution composition in a learning classifier system. DOI: 10.1145/3520304.3529014
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2021

Helena Stegherr and J?rg H?hner. 2021. Analysing metaheuristic components.
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Helena Stegherr, Michael Heider, Leopold Luley and J?rg H?hner. 2021. Design of large-scale metaheuristic component studies. DOI: 10.1145/3449726.3463168
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2020

Lukas Rosenbauer, Anthony Stein, Helena Stegherr and J?rg H?hner. 2020. Metaheuristics for the minimum set cover problem: a comparison. DOI: 10.5220/0010019901230130
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2019

Helena Stegherr, Anthony Stein and J?rg H?hner. 2019. Parallel chemical reaction optimization for utilization in intelligent RNA prediction systems.
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Curriculum/Vitae

since 2019 Research Assistant with the chair for Organic Computing
2015–2019 Bachelor programme Computer Science at the University of Augsburg
2012–2014 Master programme Biochemistry at the University of Ulm
2009–2012 Bachelor programme Biochemistry at the University of Ulm

Courses / teaching

(applied filters: semester: current | institute: Organic Computing | lecturers: Helena Stegherr | course types: all)
name semester type
Grundlagen des Organic Computing winter semester 2024/25 Vorlesung
Seminar Organic Computing (Bachelor) winter semester 2024/25 Seminar
Studentische Arbeiten am Lehrstuhl Organic Computing winter semester 2024/25 sonstige
?bung zu Grundlagen des Organic Computing winter semester 2024/25 ?bung
Seminar Organic Computing (Master) winter semester 2024/25 Seminar

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