David Pätzel

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 24

Top Topics

Machine Learning

Top Venues

GECCO Companion

SN Comput. Sci.

GECCO (Companion)

Publications

David Pätzel, Richard Nordsieck, Jörg Hähner
Length-niching Selection and Spatial Crossover in Variable-length Evolutionary Rule Set Learning. GECCO Companion (2024)
David Pätzel, Richard Nordsieck, Jörg Hähner
Measuring Similarities in Model Structure of Metaheuristic Rule Set Learners. EvoApplications@EvoStar (2024)
David Pätzel, Richard Nordsieck, Jörg Hähner
A Closer Look at Length-niching Selection and Spatial Crossover in Variable-length Evolutionary Rule Set Learning. GECCO Companion (2024)
Henning Cui, David Pätzel, Andreas Margraf, Jörg Hähner
Weighted Mutation of Connections To Mitigate Search Space Limitations in Cartesian Genetic Programming. FOGA (2023)
David Pätzel, Michael Heider, Jörg Hähner
Towards Principled Synthetic Benchmarks for Explainable Rule Set Learning Algorithms. GECCO Companion (2023)
Wenzel Pilar von Pilchau, David Pätzel, Anthony Stein, Jörg Hähner
Deep Q-Network Updates for the Full Action-Space Utilizing Synthetic Experiences. IJCNN (2023)
Michael Heider, Helena Stegherr, Roman Sraj, David Pätzel, Jonathan Wurth, Jörg Hähner
SupRB in the context of rule-based machine learning methods: A comparative study. Appl. Soft Comput. 147 (2023)
Michael Heider, Helena Stegherr, David Pätzel, Roman Sraj, Jonathan Wurth, Benedikt Volger, Jörg Hähner
Discovering Rules for Rule-Based Machine Learning with the Help of Novelty Search. SN Comput. Sci. 4 (6) (2023)
Michael Heider, David Pätzel, Alexander R. M. Wagner
An overview of LCS research from 2021 to 2022. GECCO Companion (2022)
Lukas Rosenbauer, David Pätzel, Anthony Stein, Jörg Hähner
Correction: A Learning Classifier System for Automated Test Case Prioritization and Selection. SN Comput. Sci. 3 (6) (2022)
Lukas Rosenbauer, David Pätzel, Anthony Stein, Jörg Hähner
A Learning Classifier System for Automated Test Case Prioritization and Selection. SN Comput. Sci. 3 (5) (2022)
David Pätzel, Jörg Hähner
The Bayesian learning classifier system: implementation, replicability, comparison with XCSF. GECCO (2022)
Michael Heider, Helena Stegherr, David Pätzel, Roman Sraj, Jonathan Wurth, Benedikt Volger, Jörg Hähner
Approaches for Rule Discovery in a Learning Classifier System. IJCCI (2022)
Lukas Rosenbauer, David Pätzel, Anthony Stein, Jörg Hähner
Transfer Learning for Automated Test Case Prioritization Using XCSF. EvoApplications (2021)
Lukas Rosenbauer, David Pätzel, Anthony Stein, Jörg Hähner
An Organic Computing System for Automated Testing. ARCS (2021)
David Pätzel, Michael Heider, Alexander R. M. Wagner
An overview of LCS research from 2020 to 2021. GECCO Companion (2021)
Lukas Rosenbauer, Anthony Stein, Roland Maier, David Pätzel, Jörg Hähner
XCS as a reinforcement learning approach to automatic test case prioritization. GECCO Companion (2020)
Michael Heider, David Pätzel, Jörg Hähner
SupRB: A Supervised Rule-based Learning System for Continuous Problems. CoRR (2020)
Lukas Rosenbauer, Anthony Stein, David Pätzel, Jörg Hähner
XCSF for Automatic Test Case Prioritization. IJCCI (2020)
Michael Heider, David Pätzel, Jörg Hähner
Towards a Pittsburgh-style LCS for learning manufacturing machinery parametrizations. GECCO Companion (2020)
David Pätzel, Anthony Stein, Masaya Nakata
An overview of LCS research from IWLCS 2019 to 2020. GECCO Companion (2020)
Lukas Rosenbauer, Anthony Stein, David Pätzel, Jörg Hähner
XCSF with Experience Replay for Automatic Test Case Prioritization. SSCI (2020)
David Pätzel, Anthony Stein, Jörg Hähner
A survey of formal theoretical advances regarding XCS. GECCO (Companion) (2019)
David Pätzel, Jörg Hähner
An algebraic description of XCS. GECCO (Companion) (2018)