David Pätzel

24 papers A 2B 2C 2Journal 5Unranked 13
YearRankTypeTitle / Venue / Authors
2024 — conf
A Closer Look at Length-niching Selection and Spatial Crossover in Variable-length Evolutionary Rule Set Learning.
GECCO Companion
David Pätzel, Richard Nordsieck, Jörg Hähner
2024 — conf
Length-niching Selection and Spatial Crossover in Variable-length Evolutionary Rule Set Learning.
GECCO Companion
David Pätzel, Richard Nordsieck, Jörg Hähner
2024 — conf
Measuring Similarities in Model Structure of Metaheuristic Rule Set Learners.
EvoApplications@EvoStar
David Pätzel, Richard Nordsieck, Jörg Hähner
2023 B conf
Deep Q-Network Updates for the Full Action-Space Utilizing Synthetic Experiences.
IJCNN
Wenzel Pilar von Pilchau, David Pätzel, Anthony Stein, Jörg Hähner
2023 J jnl
Discovering Rules for Rule-Based Machine Learning with the Help of Novelty Search.
SN Comput. Sci.
Michael Heider, Helena Stegherr, David Pätzel, Roman Sraj, Jonathan Wurth, Benedikt Volger, Jörg Hähner
2023 J jnl
SupRB in the context of rule-based machine learning methods: A comparative study.
Appl. Soft Comput.
Michael Heider, Helena Stegherr, Roman Sraj, David Pätzel, Jonathan Wurth, Jörg Hähner
2023 — conf
Towards Principled Synthetic Benchmarks for Explainable Rule Set Learning Algorithms.
GECCO Companion
David Pätzel, Michael Heider, Jörg Hähner
2023 A conf
Weighted Mutation of Connections To Mitigate Search Space Limitations in Cartesian Genetic Programming.
FOGA
Henning Cui, David Pätzel, Andreas Margraf, Jörg Hähner
2022 J jnl
A Learning Classifier System for Automated Test Case Prioritization and Selection.
SN Comput. Sci.
Lukas Rosenbauer, David Pätzel, Anthony Stein, Jörg Hähner
2022 — conf
An overview of LCS research from 2021 to 2022.
GECCO Companion
Michael Heider, David Pätzel, Alexander R. M. Wagner
2022 C conf
Approaches for Rule Discovery in a Learning Classifier System.
IJCCI
Michael Heider, Helena Stegherr, David Pätzel, Roman Sraj, Jonathan Wurth, Benedikt Volger, Jörg Hähner
2022 J jnl
Correction: A Learning Classifier System for Automated Test Case Prioritization and Selection.
SN Comput. Sci.
Lukas Rosenbauer, David Pätzel, Anthony Stein, Jörg Hähner
2022 A conf
The Bayesian learning classifier system: implementation, replicability, comparison with XCSF.
GECCO
David Pätzel, Jörg Hähner
2021 — conf
An Organic Computing System for Automated Testing.
ARCS
Lukas Rosenbauer, David Pätzel, Anthony Stein, Jörg Hähner
2021 — conf
An overview of LCS research from 2020 to 2021.
GECCO Companion
David Pätzel, Michael Heider, Alexander R. M. Wagner
2021 B conf
Transfer Learning for Automated Test Case Prioritization Using XCSF.
EvoApplications
Lukas Rosenbauer, David Pätzel, Anthony Stein, Jörg Hähner
2020 — conf
An overview of LCS research from IWLCS 2019 to 2020.
GECCO Companion
David Pätzel, Anthony Stein, Masaya Nakata
2020 J jnl
SupRB: A Supervised Rule-based Learning System for Continuous Problems.
CoRR
Michael Heider, David Pätzel, Jörg Hähner
2020 — conf
Towards a Pittsburgh-style LCS for learning manufacturing machinery parametrizations.
GECCO Companion
Michael Heider, David Pätzel, Jörg Hähner
2020 — conf
XCS as a reinforcement learning approach to automatic test case prioritization.
GECCO Companion
Lukas Rosenbauer, Anthony Stein, Roland Maier, David Pätzel, Jörg Hähner
2020 C conf
XCSF for Automatic Test Case Prioritization.
IJCCI
Lukas Rosenbauer, Anthony Stein, David Pätzel, Jörg Hähner
2020 — conf
XCSF with Experience Replay for Automatic Test Case Prioritization.
SSCI
Lukas Rosenbauer, Anthony Stein, David Pätzel, Jörg Hähner
2019 — conf
A survey of formal theoretical advances regarding XCS.
GECCO (Companion)
David Pätzel, Anthony Stein, Jörg Hähner
2018 — conf
An algebraic description of XCS.
GECCO (Companion)
David Pätzel, Jörg Hähner