David Pätzel

Orcid: 0000-0002-8238-8461

According to our database1, David Pätzel authored at least 22 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Measuring Similarities in Model Structure of Metaheuristic Rule Set Learners.
Proceedings of the Applications of Evolutionary Computation - 27th European Conference, 2024

2023
Discovering Rules for Rule-Based Machine Learning with the Help of Novelty Search.
SN Comput. Sci., November, 2023

SupRB in the context of rule-based machine learning methods: A comparative study.
Appl. Soft Comput., November, 2023

Deep Q-Network Updates for the Full Action-Space Utilizing Synthetic Experiences.
Proceedings of the International Joint Conference on Neural Networks, 2023

Towards Principled Synthetic Benchmarks for Explainable Rule Set Learning Algorithms.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Weighted Mutation of Connections To Mitigate Search Space Limitations in Cartesian Genetic Programming.
Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2023

2022
Correction: A Learning Classifier System for Automated Test Case Prioritization and Selection.
SN Comput. Sci., 2022

A Learning Classifier System for Automated Test Case Prioritization and Selection.
SN Comput. Sci., 2022

Approaches for Rule Discovery in a Learning Classifier System.
Proceedings of the 14th International Joint Conference on Computational Intelligence, 2022

The Bayesian learning classifier system: implementation, replicability, comparison with XCSF.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022

An overview of LCS research from 2021 to 2022.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

2021
An overview of LCS research from 2020 to 2021.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Transfer Learning for Automated Test Case Prioritization Using XCSF.
Proceedings of the Applications of Evolutionary Computation, 2021

An Organic Computing System for Automated Testing.
Proceedings of the Architecture of Computing Systems - 34th International Conference, 2021

2020
SupRB: A Supervised Rule-based Learning System for Continuous Problems.
CoRR, 2020

XCSF with Experience Replay for Automatic Test Case Prioritization.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

XCSF for Automatic Test Case Prioritization.
Proceedings of the 12th International Joint Conference on Computational Intelligence, 2020

XCS as a reinforcement learning approach to automatic test case prioritization.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

An overview of LCS research from IWLCS 2019 to 2020.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

Towards a Pittsburgh-style LCS for learning manufacturing machinery parametrizations.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

2019
A survey of formal theoretical advances regarding XCS.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019

2018
An algebraic description of XCS.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018


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