Jonathan Wurth

According to our database, Jonathan Wurth authored at least 10 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2026

Pareto-Optimal Anytime Algorithms via Bayesian Racing.

Jonathan Wurth, Helena Stegherr, Neele Kemper, Michael Heider, Jörg Hähner

CoRR, March, 2026

2025

A Comparison of Dimensionality Reduction Techniques for Visualising Search Behaviour.

Helena Stegherr, Michael Heider, Jonathan Wurth, Jörg Hähner

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2025

2024

GRAHF: A Hyper-Heuristic Framework for Evolving Heterogeneous Island Model Topologies.

Jonathan Wurth, Helena Stegherr, Michael Heider, Jörg Hähner

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

2023

Discovering Rules for Rule-Based Machine Learning with the Help of Novelty Search.

Michael Heider, Helena Stegherr, David Pätzel, Roman Sraj, Jonathan Wurth, Benedikt Volger, Jörg Hähner

SN Comput. Sci., November, 2023

SupRB in the context of rule-based machine learning methods: A comparative study.

Michael Heider, Helena Stegherr, Roman Sraj, David Pätzel, Jonathan Wurth, Jörg Hähner

Appl. Soft Comput., November, 2023

Fast, Flexible, and Fearless: A Rust Framework for the Modular Construction of Metaheuristics.

Jonathan Wurth, Helena Stegherr, Michael Heider, Leopold Luley, Jörg Hähner

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

2022

Approaches for Rule Discovery in a Learning Classifier System.

Michael Heider, Helena Stegherr, David Pätzel, Roman Sraj, Jonathan Wurth, Benedikt Volger, Jörg Hähner

Proceedings of the 14th International Joint Conference on Computational Intelligence, 2022

Comparing different metaheuristics for model selection in a supervised learning classifier system.

Jonathan Wurth, Michael Heider, Helena Stegherr, Roman Sraj, Jörg Hähner

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

Separating rule discovery and global solution composition in a learning classifier system.

Michael Heider, Helena Stegherr, Jonathan Wurth, Roman Sraj, Jörg Hähner

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

Investigating the Impact of Independent Rule Fitnesses in a Learning Classifier System.

Michael Heider, Helena Stegherr, Jonathan Wurth, Roman Sraj, Jörg Hähner

Proceedings of the Bioinspired Optimization Methods and Their Applications, 2022