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David Pätzel
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2020 – today
- 2024
- [c19]David Pätzel
, Richard Nordsieck
, Jörg Hähner
:
Measuring Similarities in Model Structure of Metaheuristic Rule Set Learners. EvoApplications@EvoStar 2024: 256-272 - [c18]David Pätzel
, Richard Nordsieck
, Jörg Hähner
:
Length-niching Selection and Spatial Crossover in Variable-length Evolutionary Rule Set Learning. GECCO Companion 2024: 303-306 - [c17]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: 1779-1787 - 2023
- [j4]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: 110706 (2023) - [j3]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): 778 (2023) - [c16]Henning Cui
, David Pätzel
, Andreas Margraf
, Jörg Hähner
:
Weighted Mutation of Connections To Mitigate Search Space Limitations in Cartesian Genetic Programming. FOGA 2023: 50-60 - [c15]David Pätzel
, Michael Heider
, Jörg Hähner
:
Towards Principled Synthetic Benchmarks for Explainable Rule Set Learning Algorithms. GECCO Companion 2023: 1657-1662 - [c14]Wenzel Pilar von Pilchau, David Pätzel, Anthony Stein, Jörg Hähner:
Deep Q-Network Updates for the Full Action-Space Utilizing Synthetic Experiences. IJCNN 2023: 1-9 - 2022
- [j2]Lukas Rosenbauer, David Pätzel, Anthony Stein, Jörg Hähner
:
A Learning Classifier System for Automated Test Case Prioritization and Selection. SN Comput. Sci. 3(5): 373 (2022) - [j1]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): 462 (2022) - [c13]David Pätzel, Jörg Hähner:
The Bayesian learning classifier system: implementation, replicability, comparison with XCSF. GECCO 2022: 413-421 - [c12]Michael Heider, David Pätzel, Alexander R. M. Wagner
:
An overview of LCS research from 2021 to 2022. GECCO Companion 2022: 2086-2094 - [c11]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: 39-49 - 2021
- [c10]Lukas Rosenbauer, David Pätzel, Anthony Stein, Jörg Hähner
:
An Organic Computing System for Automated Testing. ARCS 2021: 135-149 - [c9]Lukas Rosenbauer, David Pätzel, Anthony Stein, Jörg Hähner
:
Transfer Learning for Automated Test Case Prioritization Using XCSF. EvoApplications 2021: 681-696 - [c8]David Pätzel, Michael Heider, Alexander R. M. Wagner
:
An overview of LCS research from 2020 to 2021. GECCO Companion 2021: 1648-1656 - 2020
- [c7]Michael Heider, David Pätzel, Jörg Hähner
:
Towards a Pittsburgh-style LCS for learning manufacturing machinery parametrizations. GECCO Companion 2020: 127-128 - [c6]David Pätzel, Anthony Stein
, Masaya Nakata:
An overview of LCS research from IWLCS 2019 to 2020. GECCO Companion 2020: 1782-1788 - [c5]Lukas Rosenbauer, Anthony Stein
, Roland Maier, David Pätzel, Jörg Hähner
:
XCS as a reinforcement learning approach to automatic test case prioritization. GECCO Companion 2020: 1798-1806 - [c4]Lukas Rosenbauer, Anthony Stein, David Pätzel, Jörg Hähner
:
XCSF for Automatic Test Case Prioritization. IJCCI 2020: 49-58 - [c3]Lukas Rosenbauer, Anthony Stein, David Pätzel, Jörg Hähner
:
XCSF with Experience Replay for Automatic Test Case Prioritization. SSCI 2020: 1307-1314 - [i1]Michael Heider, David Pätzel, Jörg Hähner:
SupRB: A Supervised Rule-based Learning System for Continuous Problems. CoRR abs/2002.10295 (2020)
2010 – 2019
- 2019
- [c2]David Pätzel, Anthony Stein
, Jörg Hähner
:
A survey of formal theoretical advances regarding XCS. GECCO (Companion) 2019: 1295-1302 - 2018
- [c1]David Pätzel, Jörg Hähner
:
An algebraic description of XCS. GECCO (Companion) 2018: 1434-1441
Coauthor Index
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