2014
Temporal Difference Learning with Eligibility Traces for the Game Connect-4 Inproceedings
In: Preuss, Mike; Rudolph, Günther (Hrsg.): CIG'2014, International Conference on Computational Intelligence in Games, Dortmund, S. 84 – 91, 2014.
2013
Zukunft der Informatik Incollection
In: Becker, Klaus; others, (Hrsg.): Die Wissenschaft von der Praxis denken - Festschrift für Joachim Metzner zum 70. Geburtstag, S. 238 – 250, Verlag H. Schmidt, Mainz, 2013.
Subsampling strategies in SVM ensembles Inproceedings
In: Hoffmann, Frank; Hüllermeier, Eyke (Hrsg.): Proceedings 23. Workshop Computational Intelligence, S. 119–134, Universitätsverlag Karlsruhe, 2013.
SVM ensembles are better when different kernel types are combined Inproceedings
In: Lausen, Berthold (Hrsg.): European Conference on Data Analysis (ECDA13), GfKl, 2013.
2012
The TDMR Package: Tuned Data Mining in R Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Science and Engineering Science, no. 02/2012, 2012, (Last update: June 2017).
The TDMR Tutorial: Examples for Tuned Data Mining in R Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Science and Engineering Science, no. 03/2012, 2012, (Last update: May, 2016).
Efficient sampling and handling of variance in tuning data mining models Inproceedings
In: Coello Coello, Carlos; Cutello, Vincenzo; others, (Hrsg.): PPSN'2012: 12th International Conference on Parallel Problem Solving From Nature, Taormina, S. 195–205, Springer, Heidelberg, 2012.
Reinforcement learning with n-tuples on the game Connect-4 Inproceedings
In: Coello Coello, Carlos; Cutello, Vincenzo; others, (Hrsg.): PPSN'2012: 12th International Conference on Parallel Problem Solving From Nature, Taormina, S. 184–194, Springer, Heidelberg, 2012.
Tuning and Evolution of Support Vector Kernels Journal Article
In: Evolutionary Intelligence, vol. 5, S. 153–170, 2012.
2011
Der SFA-Algorithmus für Klassifikation Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Science and Engineering Science, no. 08/11, 2011, ISSN: 2191-365X.
SFA classification with few training data: Improvements with parametric bootstrap Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Science and Engineering Science, no. 09/11, 2011, ISSN: 2191-365X.
Ensemble-Based Modeling Technical Report
Research Center CIOP (Computational Intelligence, Optimization andData Mining) Cologne University of Applied Science, Faculty of Computer Scienceand Engineering Science, no. 06/11, 2011, ISSN: 2191-365X.
Self-configuration from a Machine-Learning Perspective Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Science and Engineering Science, no. 05/11; arXiv: 1105.1951, 2011, ISSN: 2191-365X, (e-print published at http://arxiv.org/abs/1105.1951 and Dagstuhl Preprint Archive, Workshop 11181 "Organic Computing -- Design of Self-Organizing Systems").
On the Tuning and Evolution of Support Vector Kernels Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Scienceand Engineering Science, no. 04/11, 2011, ISSN: 2191-365X.
Tuned Data Mining: A Benchmark Study on Different Tuners Technical Report
Cologne University of Applied Sciences no. 03/11, 2011.
Noisy optimization with sequential parameter optimization and optimal computational budget allocation Inproceedings
In: Proceedings of the 13th annual conference companion on Genetic and evolutionary computation, S. 119–120, ACM, Dublin, Ireland, 2011, ISBN: 978-1-4503-0690-4.
Ensemble Based Optimization and Tuning Algorithms Inproceedings
In: Hoffmann, Frank; Hüllermeier, Eyke (Hrsg.): Proceedings 21. Workshop Computational Intelligence, S. 119–134, Universitätsverlag Karlsruhe, 2011.
Tuned Data Mining in R Inproceedings
In: Hoffmann, Frank; Hüllermeier, Eyke (Hrsg.): Proceedings 21. Workshop Computational Intelligence, S. 147–160, Universitätsverlag Karlsruhe, 2011.
Tuned Data Mining: A Benchmark Study on Different Tuners Inproceedings
In: Krasnogor, Natalio (Hrsg.): GECCO '11: Proceedings of the 13th Annual Conference on Genetic andEvolutionary Computation, S. 1995–2002, 2011.
The slowness principle: SFA can detect different slow components in nonstationary time series Journal Article
In: International Journal of Innovative Computing and Applications (IJICA), vol. 3, no. 1, S. 3–10, 2011.
2010
Optimization of Biogas Production with Computational Intelligence -- A Comparative Study Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Science and Engineering Science, no. 03/10, 2010, ISSN: 2191-365X.
Comparing CI Methods for Prediction Models in Environmental Engineering Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Faculty of Computer Science and Engineering Science, Cologne University of Applied Sciences, Germany, no. 02/10, 2010, ISSN: 2191-365X.
SPOT: A Toolbox for Interactive and Automatic Tuning in the R Environment Inproceedings
In: Hoffmann, Frank; Hüllermeier, Eyke (Hrsg.): Proceedings 20. Workshop Computational Intelligence, S. 264–273, Universitätsverlag Karlsruhe, 2010.
SPOT: A Toolbox for Interactive and Automatic Tuning of Search Heuristics and Simulation Models in the R Environment Technical Report
Cologne University of Applied Sciences 2010.
Comparing SPO-tuned GP and NARX prediction models for stormwater tank fill level prediction Inproceedings
In: Fogel, Gary; others, (Hrsg.): Proc. IEEE Congress Evolutionary Computation (CEC), S. 1579–1586, 2010.
Clustering Based Niching for Genetic Programming in the R Environment Inproceedings
In: Hoffmann, Frank; Hüllermeier, Eyke (Hrsg.): Proceedings 20. Workshop Computational Intelligence, S. 33–46, Universitätsverlag Karlsruhe, 2010.
Gesture Recognition on Few Training Data using Slow Feature Analysis and Parametric Bootstrap Inproceedings
In: 2010 International Joint Conference on Neural Networks, 2010.
Optimizing Support Vector Machines for Stormwater Prediction Inproceedings
In: Bartz-Beielstein, Thomas; Chiarandini, M.; Paquete, L.; Preuss, Mike (Hrsg.): Proceedings of Workshop on Experimental Methods for the Assessment of Computational Systems joint to PPSN2010, S. 47–59, TU Dortmund, 2010.
Optimization of Support Vector Regression Models for Stormwater Prediction Inproceedings
In: Hoffmann, Frank; Hüllermeier, Eyke (Hrsg.): Proceedings 20. Workshop Computational Intelligence, S. 146–160, Universitätsverlag Karlsruhe, 2010.
Parameter-Tuned Data Mining: A General Framework Inproceedings
In: Hoffmann, Frank; Hüllermeier, Eyke (Hrsg.): Proceedings 20. Workshop Computational Intelligence, Universitätsverlag Karlsruhe, 2010.
How slow is slow? SFA detects signals that are slower than the driving force Inproceedings
In: Filipic, Bogdan; Silc, Juri (Hrsg.): Proc. 4th Int. Conf. on Bioinspired Optimization Methods and their Applications, BIOMA, Ljubljana, Slovenia, 2010.
Optimization of Biogas Production with Computational Intelligence -- A Comparative Study Inproceedings
In: Fogel, Gary; others, (Hrsg.): Proc. 2010 Congress on Evolutionary Computation (CEC'10) within IEEE World Congress on Computational Intelligence (WCCI'10), Barcelona, Spain, S. 3606–3613, IEEE Press, Piscataway NJ, 2010.
2009
How slow is slow? SFA detects signals that are slower than the driving force Technical Report
Cologne University of Applied Sciences no. 05/09, 2009, (e-print published at http://arxiv.org/abs/0911.4397).
On the numeric stability of the SFA implementation sfa-tk Technical Report
Cologne University of Applied Sciences no. 05/10, 2009, (e-print published at http://arxiv.org/abs/0912.1064).
Genetic Programming Applied to Predictive Control in Environmental Engineering Inproceedings
In: Hoffmann, Frank; Hüllermeier, Eyke (Hrsg.): Proceedings 19. Workshop Computational Intelligence, S. 101–113, KIT Scientific Publishing, Karlsruhe, 2009.
Optischer Fluss und Image Mosaicing nach Kourogi Technical Report
Cologne University of Applied Sciences 2009, (In German).
Reinforcement learning for games: failures and successes -- CMA-ES and TDL in comparision Inproceedings
In: GECCO '09: Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference, S. 2641–2648, ACM, Montreal, Québec, Canada, 2009.
Optimized Modelling of Fill Levels in Stormwater Tanks Using CI-based Parameter Selection Schemes (in german) Journal Article
In: at-Automatisierungstechnik, vol. 57, no. 3, S. 155–166, 2009.
Evolutionsstrategien und Reinforcement Learning für strategische Brettspiele Technical Report
Cologne University of Applied Sciences 2009.
2008
Reinforcement Learning: Insights from Interesting Failures in Parameter Selection Inproceedings
In: Rudolph, Günter; others, (Hrsg.): PPSN'2008: 10th International Conference on Parallel Problem Solving From Nature, Dortmund, S. 478–487, Springer, Berlin, 2008.
Parameterselektion für komplexe Modellierungsaufgaben der Wasserwirtschaft -- Moderne CI-Verfahren zur Zeitreihenanalyse Inproceedings
In: Mikut, Ralf; Reischl, Markus (Hrsg.): Proc. 18th Workshop Computational Intelligence, S. 136–150, Universitätsverlag, Karlsruhe, 2008.
Moderne statistische Verfahren zur Parameteroptimierung und systematischen Modellauswahl Technical Report
Cologne University of Applied Sciences 2008.
Genetisches Programmieren für Vorhersagemodelle in der Finanzwirtschaft Technical Report
Cologne University of Applied Sciences 2008.
Datenanalyse und Prozessoptimierung am Beispiel Kläranlagen Technical Report
Cologne University of Applied Sciences 2008.
Reinforcement Learning für Brettspiele: Der Temporal Difference Algorithmus Technical Report
Cologne University of Applied Sciences 2008.
Reinforcement Learning für strategische Brettspiele Technical Report
Cologne University of Applied Sciences 2008.
Internationaler DATA-MINING-CUP (DMC) mit studentischer Beteiligung des Campus Gummersbach Technical Report
Cologne University of Applied Sciences 2008.
2007
Robust registration procedures for endoscopic imaging Journal Article
In: Medical Image Analysis, vol. 11, no. 6, S. 526-539, 2007.
Computational Intelligence und Data Mining -- Portfoliooptimierung unter Nebenbedingungen Technical Report
Cologne University of Applied Sciences 2007.
Computational Intelligence und Data Mining -- Moderne statistische Verfahren zur experimentellen Versuchsplanung Technical Report
FH Köln 2007.
Suchfeld
Entwicklung einer allgemeinen Schnittstelle zwischen Ludii und dem GBG Framework Technical Report
TH Köln -- University of Applied Sciences 2022, (Praxisprojekt).
Sample-based Rule Extraction for Explainable Reinforcement Learning Inproceedings
In: 8th International Conference on machine Learning, Optimization, and Data Science (LOD2022), 2022.
AlphaZero-Inspired Game Learning: Faster Training by Using MCTS Only at Test Time Journal Article
In: IEEE Transactions on Games, 2022.
AlphaZero-Inspired Game Learning: Faster Training by Using MCTS Only at Test Time Journal Article
In: arXiv preprint arXiv:2204.13307, 2022, (Preprint of the IEEE ToG 2022 paper).
TH Köln -- University of Applied Sciences, 2021, (Bachelor thesis).
Portierung einer Java-Reaktorsimulation nach Python und Performanz-Vergleich mit verschiedenen Python-Java-Bridges Technical Report
TH Köln -- University of Applied Sciences 2021, (Projekt).
Reinforcement Learning am realen und simulierten Cart-Pole-Swing-Up Pendulum im Vergleich Masters Thesis
TH Köln -- University of Applied Sciences, 2021, (Bachelor thesis).
TH Köln -- University of Applied Sciences, 2021, (Bachelor thesis).
Untersuchung von allgemeinen KI-Agenten für das Spiel Poker im General Board Games Framework Masters Thesis
TH Köln -- University of Applied Sciences, 2021, (Master thesis).
Erstellung eines Custom Environments in OpenAI Gym für das Spiel Ökolopoly Technical Report
TH Köln -- University of Applied Sciences 2021, (Praxisprojekt).