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Bagheri, Samineh; Konen, Wolfgang; Emmerich, Michael; Bäck, Thomas
Self-adjusting parameter control for surrogate-assisted constrained optimization under limited budgets Artikel
In: Applied Soft Computing, Bd. 61, S. 377–393, 2017, ISSN: 1568-4946.
@article{Bagh17bb,
title = {Self-adjusting parameter control for surrogate-assisted constrained optimization under limited budgets},
author = {Samineh Bagheri and Wolfgang Konen and Michael Emmerich and Thomas Bäck},
url = {http://www.sciencedirect.com/science/article/pii/S1568494617304805},
doi = {https://doi.org/10.1016/j.asoc.2017.07.060},
issn = {1568-4946},
year = {2017},
date = {2017-01-01},
journal = {Applied Soft Computing},
volume = {61},
pages = {377--393},
keywords = {CI, constraints, MONREP, optimization, SACOBRA, surrogate models},
pubstate = {published},
tppubtype = {article}
}
Galitzki, Kevin
Selbstlernende Agenten für das skalierbare Spiel Hex: Untersuchung verschiedener KI-Verfahren im GBG-Framework Abschlussarbeit
TH Köln -- University of Applied Sciences, 2017, (Bachelor thesis).
@mastersthesis{Galitzki2017,
title = {Selbstlernende Agenten für das skalierbare Spiel Hex: Untersuchung verschiedener KI-Verfahren im GBG-Framework},
author = {Kevin Galitzki},
url = {http://www.gm.fh-koeln.de/~konen/research/PaperPDF/BA-KevinGalitzki-final-2017.pdf},
year = {2017},
date = {2017-01-01},
institution = {Institut für Informatik},
school = {TH Köln -- University of Applied Sciences},
note = {Bachelor thesis},
keywords = {BT-MT, CI, Game Learning, GBG, learning, optimization, Reinforcement learning},
pubstate = {published},
tppubtype = {mastersthesis}
}
Kutsch, Johannes
KI-Agenten fur das Spiel 2048: Untersuchung von Lernalgorithmen für nichtdeterministische Spiele Abschlussarbeit
TH Köln -- University of Applied Sciences, 2017, (Bachelor thesis).
@mastersthesis{Kutsch2017,
title = {KI-Agenten fur das Spiel 2048: Untersuchung von Lernalgorithmen für nichtdeterministische Spiele},
author = {Johannes Kutsch},
url = {http://www.gm.fh-koeln.de/~konen/research/PaperPDF/BA_JohannesKutsch_Final-2017.pdf},
year = {2017},
date = {2017-01-01},
institution = {Institut für Informatik},
school = {TH Köln -- University of Applied Sciences},
note = {Bachelor thesis},
keywords = {BT-MT, CI, Game Learning, GBG, learning, optimization, Reinforcement learning},
pubstate = {published},
tppubtype = {mastersthesis}
}
Thill, Markus; Konen, Wolfgang; Bäck, Thomas
Online anomaly detection on the Webscope S5 dataset: A comparative study Proceedings Article
In: IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2017), S. 1, Springer 2017.
@inproceedings{Thill17a-SORAD,
title = {Online anomaly detection on the Webscope S5 dataset: A comparative study},
author = {Markus Thill and Wolfgang Konen and Thomas Bäck},
url = {http://www.gm.fh-koeln.de/ciopwebpub/Thill17a.d/Thill17a-SORAD.pdf},
year = {2017},
date = {2017-01-01},
booktitle = {IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2017)},
pages = {1},
organization = {Springer},
keywords = {anomaly detection, time series},
pubstate = {published},
tppubtype = {inproceedings}
}
2016
Bagheri, Samineh; Konen, Wolfgang; Bäck, Thomas
Online Selection of Surrogate Models for Constrained Black-Box Optimization Proceedings Article
In: Jin, Yaochu (Hrsg.): SSCI'2016, Athens, S. 1, IEEE, 2016, (Best Student Paper Award).
@inproceedings{Bagh16c,
title = {Online Selection of Surrogate Models for Constrained Black-Box Optimization},
author = {Samineh Bagheri and Wolfgang Konen and Thomas Bäck},
editor = {Yaochu Jin},
url = {http://www.gm.fh-koeln.de/~konen/Publikationen/Bagh16-SSCI.pdf},
year = {2016},
date = {2016-12-01},
booktitle = {SSCI'2016, Athens},
pages = {1},
publisher = {IEEE},
note = {Best Student Paper Award},
keywords = {CI, constraints, ensemble, MONREP, optimization, SACOBRA},
pubstate = {published},
tppubtype = {inproceedings}
}
Bagheri, Samineh; Konen, Wolfgang; Bäck, Thomas
Equality Constraint Handling for Surrogate-Assisted Constrained Optimization Proceedings Article
In: Tan, Kay Chen (Hrsg.): WCCI'2016, Vancouver, S. 1, IEEE, 2016.
@inproceedings{Bagh16a,
title = {Equality Constraint Handling for Surrogate-Assisted Constrained Optimization},
author = {Samineh Bagheri and Wolfgang Konen and Thomas Bäck},
editor = {Kay Chen Tan},
url = {http://www.gm.fh-koeln.de/~konen/Publikationen/Bagh16-WCCI.pdf},
year = {2016},
date = {2016-07-01},
booktitle = {WCCI'2016, Vancouver},
pages = {1},
publisher = {IEEE},
keywords = {CI, constraints, MONREP, optimization, SACOBRA},
pubstate = {published},
tppubtype = {inproceedings}
}
2015
Bagheri, Samineh; Konen, Wolfgang; Foussette, Christophe; Krause, Peter; Bäck, Thomas; Koch, Patrick
SACOBRA: Self-Adjusting Constrained Black-Box Optimization with RBF Proceedings Article
In: Hoffmann, Frank; Hüllermeier, Eyke (Hrsg.): Proceedings 25. Workshop Computational Intelligence, S. 87-98, Universitätsverlag Karlsruhe, 2015, (Young Author Award GMA-CI).
@inproceedings{Bagh15b,
title = {SACOBRA: Self-Adjusting Constrained Black-Box Optimization with RBF},
author = {Samineh Bagheri and Wolfgang Konen and Christophe Foussette and Peter Krause and Thomas Bäck and Patrick Koch},
editor = {Frank Hoffmann and Eyke Hüllermeier},
url = {http://www.gm.fh-koeln.de/~konen/Publikationen/Bagh15-GMA-CI.pdf},
year = {2015},
date = {2015-11-01},
booktitle = {Proceedings 25. Workshop Computational Intelligence},
pages = {87-98},
publisher = {Universitätsverlag Karlsruhe},
note = {Young Author Award GMA-CI},
keywords = {CI, constraints, MONREP, optimization},
pubstate = {published},
tppubtype = {inproceedings}
}
Konen, Wolfgang
Reinforcement Learning for Board Games: The Temporal Difference Algorithm Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Sciences, 2015.
@techreport{Kone15c,
title = {Reinforcement Learning for Board Games: The Temporal Difference Algorithm},
author = {Konen, Wolfgang},
url = {http://www.gm.fh-koeln.de/ciopwebpub/Kone15c.d/TR-TDgame_EN.pdf},
year = {2015},
date = {2015-07-01},
address = {Cologne University of Applied Sciences},
institution = {Research Center CIOP (Computational Intelligence, Optimization and Data Mining)},
keywords = {Game Learning, learning, Reinforcement learning},
pubstate = {published},
tppubtype = {techreport}
}
Koch, Patrick; Wagner, Tobias; Emmerich, Michael; Bäck, Thomas; Konen, Wolfgang
Efficient multi-criteria optimization on noisy machine learning problems Artikel
In: Applied Soft Computing, Bd. 29, S. 357-370, 2015.
@article{Koch15,
title = {Efficient multi-criteria optimization on noisy machine learning problems},
author = {Patrick Koch and Tobias Wagner and Michael Emmerich and Thomas Bäck and Wolfgang Konen},
url = {http://www.sciencedirect.com/science/article/pii/S156849461500006X#},
doi = {https://doi.org/10.1016/j.asoc.2015.01.005},
year = {2015},
date = {2015-05-01},
journal = {Applied Soft Computing},
volume = {29},
pages = {357-370},
keywords = {machine learning, TDMR},
pubstate = {published},
tppubtype = {article}
}
Bagheri, Samineh; Thill, Markus; Koch, Patrick; Konen, Wolfgang
Online Adaptable Learning Rates for the Game Connect-4 Artikel
In: IEEE Transactions on Computational Intelligence and AI in Games, Bd. (accepted 11/2014), S. 1, 2015.
@article{Bagh15,
title = {Online Adaptable Learning Rates for the Game Connect-4},
author = {Samineh Bagheri and Markus Thill and Patrick Koch and Wolfgang Konen},
url = {http://dx.doi.org/10.1109/TCIAIG.2014.2367105},
year = {2015},
date = {2015-01-01},
journal = {IEEE Transactions on Computational Intelligence and AI in Games},
volume = {(accepted 11/2014)},
pages = {1},
keywords = {Game Learning, learning, Reinforcement learning},
pubstate = {published},
tppubtype = {article}
}
Koch, Patrick; Bagheri, Samineh; Konen, Wolfgang; Foussette, Christophe; Krause, Peter; Bäck, Thomas
A New Repair Method For Constrained Optimization Proceedings Article
In: Jiménez-Laredo, Juan Luis (Hrsg.): Proceedings of the 17th Genetic and Evolutionary Computation Conference, 2015, (accepted).
@inproceedings{Koch15a,
title = {A New Repair Method For Constrained Optimization},
author = {Patrick Koch and Samineh Bagheri and Wolfgang Konen and Christophe Foussette and Peter Krause and Thomas Bäck},
editor = {Juan Luis Jiménez-Laredo},
year = {2015},
date = {2015-01-01},
booktitle = {Proceedings of the 17th Genetic and Evolutionary Computation Conference},
series = {GECCO'15},
note = {accepted},
keywords = {constraint, MONREP, optimization},
pubstate = {published},
tppubtype = {inproceedings}
}
Konen, Wolfgang
Reinforcement Learning für Brettspiele: Der Temporal Difference Algorithmus Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Sciences, 2015, (Updated version 2015).
@techreport{Kone15a,
title = {Reinforcement Learning für Brettspiele: Der Temporal Difference Algorithmus},
author = {Wolfgang Konen},
url = {http://www.gm.fh-koeln.de/ciopwebpub/Kone15a.d/TR-TDgame.pdf},
year = {2015},
date = {2015-01-01},
address = {Cologne University of Applied Sciences},
institution = {Research Center CIOP (Computational Intelligence, Optimization and Data Mining)},
note = {Updated version 2015},
keywords = {Game Learning, learning, Reinforcement learning},
pubstate = {published},
tppubtype = {techreport}
}
Konen, Wolfgang
The rCMA Tutorial: Examples for using CMA-ES in R Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, 2015.
@techreport{Kone15b,
title = {The rCMA Tutorial: Examples for using CMA-ES in R},
author = {Konen, Wolfgang},
url = {http://www.gm.fh-koeln.de/ciopwebpub/Kone15b.d/rCMA-tutorial.pdf},
year = {2015},
date = {2015-00-01},
address = {Cologne University of Applied Science},
institution = {Research Center CIOP (Computational Intelligence, Optimization and Data Mining)},
keywords = {constraint, MONREP, optimization, rCMA},
pubstate = {published},
tppubtype = {techreport}
}
2014
Bagheri, Samineh; Thill, Markus; Koch, Patrick; Konen, Wolfgang
Online Adaptable Learning Rates for the Game Connect-4 Forschungsbericht
CIplus Nr. TR 03/2014, 2014, (Preprint version of the article in IEEE Transactions on Computational Intelligence and AI in Games, 2015).
@techreport{Bagh14a,
title = {Online Adaptable Learning Rates for the Game Connect-4},
author = {Samineh Bagheri and Markus Thill and Patrick Koch and Wolfgang Konen},
url = {http://nbn-resolving.de/urn:nbn:de:hbz:832-cos-704},
year = {2014},
date = {2014-01-01},
number = {TR 03/2014},
institution = {CIplus},
note = {Preprint version of the article in IEEE Transactions on Computational Intelligence and AI in Games, 2015},
keywords = {Game Learning, learning, Reinforcement learning},
pubstate = {published},
tppubtype = {techreport}
}
Koch, Patrick; Bagheri, Samineh; Foussette, Christophe; Krause, Peter; Bäck, Thomas; Konen, Wolfgang
Constrained Optimization with a Limited Number of Function Evaluations Proceedings Article
In: Hoffmann, Frank; Hüllermeier, Eyke (Hrsg.): Proceedings 24. Workshop Computational Intelligence, S. 119–134, Universitätsverlag Karlsruhe, 2014, (Young Author Award GMA-CI).
@inproceedings{Koch14a,
title = {Constrained Optimization with a Limited Number of Function Evaluations},
author = {Patrick Koch and Samineh Bagheri and Christophe Foussette and Peter Krause and Thomas Bäck and Wolfgang Konen },
editor = {Frank Hoffmann and Eyke Hüllermeier},
url = {http://www.gm.fh-koeln.de/~konen/Publikationen/Koch2014a-GMA-CI.pdf},
year = {2014},
date = {2014-01-01},
booktitle = {Proceedings 24. Workshop Computational Intelligence},
pages = {119--134},
publisher = {Universitätsverlag Karlsruhe},
note = {Young Author Award GMA-CI},
keywords = {MONREP, optimization},
pubstate = {published},
tppubtype = {inproceedings}
}
Konen, Wolfgang; Koch, Patrick
Adaptation in Nonlinear Learning Models for Nonstationary Tasks Proceedings Article
In: Filipic, Bogdan (Hrsg.): PPSN'2014: 13th International Conference on Parallel Problem Solving From Nature, Ljubljana, Springer, Heidelberg, 2014.
@inproceedings{Kone14a,
title = {Adaptation in Nonlinear Learning Models for Nonstationary Tasks},
author = {Wolfgang Konen and Patrick Koch},
editor = {Bogdan Filipic},
url = {http://maanvs03.gm.fh-koeln.de/webpub/CIOPReports.d/Kone14a.d/Kone14a.pdf},
year = {2014},
date = {2014-01-01},
booktitle = {PPSN'2014: 13th International Conference on Parallel Problem Solving From Nature, Ljubljana},
publisher = {Springer},
address = {Heidelberg},
keywords = {Game Learning, learning, Reinforcement learning},
pubstate = {published},
tppubtype = {inproceedings}
}
Liebig, Kay N.; Maslehaty, Homajoun; Petridis, Athanasios K.; Konen, Wolfgang; Scholz, Martin
Comparison of two algorithms for the application of real time image mosaicking in neuroendoscopy Artikel
In: Journal of Neurosurgery, Bd. 121, Nr. 3, S. 688 – 699, 2014.
@article{Lieb14,
title = {Comparison of two algorithms for the application of real time image mosaicking in neuroendoscopy},
author = {Kay N. Liebig and Homajoun Maslehaty and Athanasios K. Petridis and Wolfgang Konen and Martin Scholz},
year = {2014},
date = {2014-01-01},
journal = {Journal of Neurosurgery},
volume = {121},
number = {3},
pages = {688 -- 699},
abstract = {OBJECT: Neuroendoscopy is used more and more frequently in neurosurgical procedures and has become an important tool in the neurosurgical armamentarium. However, the main restriction of neuroendoscopy is the limited field of view. A better overview of the area of interest would increase surgical safety and decrease procedure-related morbidity rates. In the present study, the authors aimed to improve this restriction by using and comparing two algorithms to create endoscopic panoramic images, which increase the field of view during neuroendoscopic procedures. METHODS: Different endoscopic methods with or without a stand and with linear or circular endoscope movements were performed in cadaveric ventricles. Video of the endoscopy was used to create image mosaics of the lateral ventricle with the help of the Kourogi or LogSearch (LS) algorithm. In the LS algorithm, different template sizes were used. Three observers graded the quality of the image mosaic in terms of usefulness in surgery. The fastest frame rate was 3-4 frames/second. RESULTS: The LS algorithm with a larger template size showed significantly better results for the creation of image mosaics than the Kourogi algorithm in linear endoscopic movement with or without a stand. In circular endoscopic movements, the results seemed to be better with the LS algorithm but were not significantly different from those obtained with the Kourogi algorithm. In summary, image quality in the experimental paradigms was satisfying. CONCLUSIONS: Results in the study showed that the creation of image mosaics is possible and reliable with the featured algorithms. Image mosaicking is an applicable device for neuroendoscopy and can increase the field of view during endoscopic procedures. Its use can increase the safety and the field of application of neuroendoscopy. However, faster frame rates will be required to create a smooth image for practical use during surgery.},
keywords = {BV-3D-Endo, computer vision, image mosaic, LogSearch algorithm, neuroendoscopy},
pubstate = {published},
tppubtype = {article}
}
OBJECT: Neuroendoscopy is used more and more frequently in neurosurgical procedures and has become an important tool in the neurosurgical armamentarium. However, the main restriction of neuroendoscopy is the limited field of view. A better overview of the area of interest would increase surgical safety and decrease procedure-related morbidity rates. In the present study, the authors aimed to improve this restriction by using and comparing two algorithms to create endoscopic panoramic images, which increase the field of view during neuroendoscopic procedures. METHODS: Different endoscopic methods with or without a stand and with linear or circular endoscope movements were performed in cadaveric ventricles. Video of the endoscopy was used to create image mosaics of the lateral ventricle with the help of the Kourogi or LogSearch (LS) algorithm. In the LS algorithm, different template sizes were used. Three observers graded the quality of the image mosaic in terms of usefulness in surgery. The fastest frame rate was 3-4 frames/second. RESULTS: The LS algorithm with a larger template size showed significantly better results for the creation of image mosaics than the Kourogi algorithm in linear endoscopic movement with or without a stand. In circular endoscopic movements, the results seemed to be better with the LS algorithm but were not significantly different from those obtained with the Kourogi algorithm. In summary, image quality in the experimental paradigms was satisfying. CONCLUSIONS: Results in the study showed that the creation of image mosaics is possible and reliable with the featured algorithms. Image mosaicking is an applicable device for neuroendoscopy and can increase the field of view during endoscopic procedures. Its use can increase the safety and the field of application of neuroendoscopy. However, faster frame rates will be required to create a smooth image for practical use during surgery.
Thill, Markus; Bagheri, Samineh; Koch, Patrick; Konen, Wolfgang
Temporal Difference Learning with Eligibility Traces for the Game Connect-4 Proceedings Article
In: Preuss, Mike; Rudolph, Günther (Hrsg.): CIG'2014, International Conference on Computational Intelligence in Games, Dortmund, 2014.
@inproceedings{Thil14,
title = {Temporal Difference Learning with Eligibility Traces for the Game Connect-4},
author = {Markus Thill and Samineh Bagheri and Patrick Koch and Wolfgang Konen},
editor = {Mike Preuss and Günther Rudolph},
url = {http://www.gm.fh-koeln.de/~konen/Publikationen/ThillCIG2014.pdf},
year = {2014},
date = {2014-01-01},
booktitle = {CIG'2014, International Conference on Computational Intelligence in Games, Dortmund},
keywords = {Game Learning, learning, Reinforcement learning},
pubstate = {published},
tppubtype = {inproceedings}
}
Thill, Markus; Konen, Wolfgang
Connect-4 Game Playing Framework (C4GPF) Sonstige
2014.
@misc{ThilKon14,
title = {Connect-4 Game Playing Framework (C4GPF)},
author = {Markus Thill and Wolfgang Konen},
url = {http://github.com/MarkusThill/Connect-Four},
year = {2014},
date = {2014-01-01},
keywords = {Game Learning, learning, Reinforcement learning},
pubstate = {published},
tppubtype = {misc}
}
2013
Faeskorn-Woyke, Heide; Konen, Wolfgang; Stahl, Hans
Zukunft der Informatik Buchabschnitt
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.
@incollection{Faes13,
title = {Zukunft der Informatik},
author = {Heide Faeskorn-Woyke and Wolfgang Konen and Hans Stahl},
editor = {Klaus Becker and others},
url = {http://www.gm.fh-koeln.de/~konen/Publikationen/Festschrift-Metzner2013.pdf},
year = {2013},
date = {2013-01-01},
booktitle = {Die Wissenschaft von der Praxis denken - Festschrift für Joachim Metzner zum 70. Geburtstag},
pages = {238 -- 250},
publisher = {Verlag H. Schmidt, Mainz},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
Koch, Patrick; Konen, Wolfgang
Subsampling strategies in SVM ensembles Proceedings Article
In: Hoffmann, Frank; Hüllermeier, Eyke (Hrsg.): Proceedings 23. Workshop Computational Intelligence, S. 119–134, Universitätsverlag Karlsruhe, 2013.
@inproceedings{Koch13a,
title = {Subsampling strategies in SVM ensembles},
author = {Patrick Koch and Wolfgang Konen},
editor = {Frank Hoffmann and Eyke Hüllermeier},
url = {http://www.gm.fh-koeln.de/~konen/Publikationen/kochGMA2013.pdf},
year = {2013},
date = {2013-01-01},
booktitle = {Proceedings 23. Workshop Computational Intelligence},
pages = {119--134},
publisher = {Universitätsverlag Karlsruhe},
keywords = {SOMA, TDMR},
pubstate = {published},
tppubtype = {inproceedings}
}
Stork, Jörg; Ramos, Ricardo; Koch, Patrick; Konen, Wolfgang
SVM ensembles are better when different kernel types are combined Proceedings Article
In: Lausen, Berthold (Hrsg.): European Conference on Data Analysis (ECDA13), (under review), 2013.
@inproceedings{stork13a,
title = {SVM ensembles are better when different kernel types are combined},
author = {Jörg Stork and Ricardo Ramos and Patrick Koch and Wolfgang Konen},
editor = {Berthold Lausen},
url = {http://www.gm.fh-koeln.de/~konen/Publikationen/storkECDA-2013.pdf},
year = {2013},
date = {2013-01-01},
booktitle = {European Conference on Data Analysis (ECDA13)},
publisher = {(under review)},
keywords = {SOMA, TDMR},
pubstate = {published},
tppubtype = {inproceedings}
}
Guerra, Ricardo Ramos; Stork, Jörg
Building and analyzing SVM ensembles with Bagging and AdaBoost on big data sets Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Sciences, Nr. 1/13, 2013.
@techreport{Ramos13a,
title = {Building and analyzing SVM ensembles with Bagging and AdaBoost on big data sets},
author = {Ricardo Ramos Guerra and Jörg Stork},
url = {http://maanvs03.gm.fh-koeln.de/webpub/CIOPReports.d/Ramos13a.d/Ramos13a.pdf},
year = {2013},
date = {2013-01-01},
number = {1/13},
address = {Cologne University of Applied Sciences},
institution = {Research Center CIOP (Computational Intelligence, Optimization and Data Mining)},
keywords = {SVM},
pubstate = {published},
tppubtype = {techreport}
}
2012
Konen, Wolfgang; Koch, Patrick
The TDMR Package: Tuned Data Mining in R Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Science and Engineering Science, Nr. 02/2012, 2012, (Last update: June 2017).
@techreport{Kone12ac,
title = {The TDMR Package: Tuned Data Mining in R},
author = {Wolfgang Konen and Patrick Koch},
url = {http://www.gm.fh-koeln.de/ciopwebpub/Kone12a.d/Kone12a-V2017-07.pdf},
year = {2012},
date = {2012-11-01},
number = {02/2012},
address = {Cologne University of Applied Science, Faculty of Computer Science and Engineering Science},
institution = {Research Center CIOP (Computational Intelligence, Optimization and Data Mining)},
note = {Last update: June 2017},
keywords = {parameter tuning, SOMA, TDMR},
pubstate = {published},
tppubtype = {techreport}
}
Konen, Wolfgang; Koch, Patrick
The TDMR Tutorial: Examples for Tuned Data Mining in R Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Science and Engineering Science, Nr. 03/2012, 2012, (Last update: May, 2016).
@techreport{Kone12bb,
title = {The TDMR Tutorial: Examples for Tuned Data Mining in R},
author = {Wolfgang Konen and Patrick Koch},
url = {http://www.gm.fh-koeln.de/ciopwebpub/Kone12b.d/Kone12b-V2016-05.pdf},
year = {2012},
date = {2012-11-01},
number = {03/2012},
address = {Cologne University of Applied Science, Faculty of Computer Science and Engineering Science},
institution = {Research Center CIOP (Computational Intelligence, Optimization and Data Mining)},
note = {Last update: May, 2016},
keywords = {parameter tuning, SOMA, TDMR},
pubstate = {published},
tppubtype = {techreport}
}
Thill, Markus
Reinforcement Learning mit N-Tupel-Systemen für Vier Gewinnt Abschlussarbeit
TH Köln – University of Applied Sciences, 2012, (Bachelor thesis, 1st prize in Opitz award 2013, Festo award 2012, Ferchau award 2012).
@mastersthesis{Thill2012,
title = {Reinforcement Learning mit N-Tupel-Systemen für Vier Gewinnt},
author = {Markus Thill},
url = {http://www.gm.fh-koeln.de/ciopwebpub/Theses.d/Thill12.d/BA-Thill-2012.pdf},
year = {2012},
date = {2012-07-01},
school = {TH Köln – University of Applied Sciences},
note = {Bachelor thesis, 1st prize in Opitz award 2013, Festo award 2012, Ferchau award 2012},
keywords = {board games, BT-MT, Game Learning, learning},
pubstate = {published},
tppubtype = {mastersthesis}
}
Flasch, Oliver; Bartz-Beielstein, Thomas
A Framework for the Empirical Analysis of Genetic Programming System Performance Buchabschnitt
In: Riolo, Rick; Vladislavleva, Ekaterina; Moore, Jason H. (Hrsg.): Genetic Programming Theory and Practice X, S. TBA, Springer, Ann Arbor, USA, 2012.
@incollection{Flas12c,
title = {A Framework for the Empirical Analysis of Genetic Programming System Performance},
author = {Oliver Flasch and Thomas Bartz-Beielstein},
editor = {Rick Riolo and Ekaterina Vladislavleva and Jason H. Moore},
year = {2012},
date = {2012-01-01},
booktitle = {Genetic Programming Theory and Practice X},
pages = {TBA},
publisher = {Springer},
address = {Ann Arbor, USA},
chapter = {TBA},
series = {Genetic and Evolutionary Computation},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
Flasch, Oliver; Bartz-Beielstein, Thomas
Towards a Framework for the Empirical Analysis of Genetic Programming System Performance Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Faculty of Computer Science and Engineering Science, Cologne University of Applied Sciences, Germany, Nr. 05/12, 2012, ISSN: 2191-365X.
@techreport{Flas12a,
title = {Towards a Framework for the Empirical Analysis of Genetic Programming System Performance},
author = {Oliver Flasch and Thomas Bartz-Beielstein},
url = {http://maanvs03.gm.fh-koeln.de/webpub/CIOPReports.d/Flas12a.d/ciop0512.pdf},
issn = {2191-365X},
year = {2012},
date = {2012-01-01},
number = {05/12},
address = {Faculty of Computer Science and Engineering Science, Cologne University of Applied Sciences, Germany},
institution = {Research Center CIOP (Computational Intelligence, Optimization and Data Mining)},
keywords = {GP},
pubstate = {published},
tppubtype = {techreport}
}
Friese, Martina; Bartz-Beielstein, Thomas; Vladislavleva, Katya; Flasch, Oliver; Mersmann, Olaf; Naujoks, Boris; Stork, Jörg; Zaefferer, Martin
Ensemble-Based Model Selection for Smart Metering Data (Abstract) Forschungsbericht
CIplus 2012.
@techreport{Frie12a,
title = {Ensemble-Based Model Selection for Smart Metering Data (Abstract)},
author = {Martina Friese and Thomas Bartz-Beielstein and Katya Vladislavleva and Oliver Flasch and Olaf Mersmann and Boris Naujoks and Jörg Stork and Martin Zaefferer},
year = {2012},
date = {2012-01-01},
institution = {CIplus},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
Koch, Patrick; Konen, Wolfgang
Efficient sampling and handling of variance in tuning data mining models Proceedings Article
In: Coello, Carlos A. Coello; Cutello, Vincenzo; others, (Hrsg.): PPSN'2012: 12th International Conference on Parallel Problem Solving From Nature, Taormina, S. 195–205, Springer, Heidelberg, 2012.
@inproceedings{Koch12ab,
title = {Efficient sampling and handling of variance in tuning data mining models},
author = {Patrick Koch and Wolfgang Konen},
editor = {Carlos A. Coello Coello and Vincenzo Cutello and others},
url = {http://maanvs03.gm.fh-koeln.de/webpub/CIOPReports.d/Koch12a.d/Koch12a.pdf},
year = {2012},
date = {2012-01-01},
booktitle = {PPSN'2012: 12th International Conference on Parallel Problem Solving From Nature, Taormina},
pages = {195--205},
publisher = {Springer},
address = {Heidelberg},
keywords = {SOMA, TDMR},
pubstate = {published},
tppubtype = {inproceedings}
}
Koch, Patrick; Bischl, Bernd; Flasch, Oliver; Bartz-Beielstein, Thomas; Weihs, Claus; Konen, Wolfgang
Tuning and Evolution of Support Vector Kernels Artikel
In: Evolutionary Intelligence, Bd. 5, S. 153–170, 2012.
@article{Koch11aa,
title = {Tuning and Evolution of Support Vector Kernels},
author = {Patrick Koch and Bernd Bischl and Oliver Flasch and Thomas Bartz-Beielstein and Claus Weihs and Wolfgang Konen},
url = {http://www.gm.fh-koeln.de/~konen/Publikationen/Koch11a-EvolIntel.pdf},
year = {2012},
date = {2012-01-01},
journal = {Evolutionary Intelligence},
volume = {5},
pages = {153--170},
keywords = {SOMA, TDMR},
pubstate = {published},
tppubtype = {article}
}
Konen, Wolfgang; Koch, Patrick
The TDMR Framework: Tuned Data Mining in R Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Science and Engineering Science, Nr. 02/2012, 2012.
@techreport{Kone12ab,
title = {The TDMR Framework: Tuned Data Mining in R},
author = {Wolfgang Konen and Patrick Koch},
url = {http://www.gm.fh-koeln.de/ciopwebpub/Kone12a.d/Kone12a.pdf},
year = {2012},
date = {2012-01-01},
number = {02/2012},
address = {Cologne University of Applied Science, Faculty of Computer Science and Engineering Science},
institution = {Research Center CIOP (Computational Intelligence, Optimization and Data Mining)},
keywords = {SOMA, TDMR},
pubstate = {published},
tppubtype = {techreport}
}
Thill, Markus
Einsatz von N-Tupel-Systemen mit TD-Learning für strategische Brettspiele am Beispiel von Vier Gewinnt Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Science and Engineering Science, Nr. 01/12, 2012, ISSN: 2191-365X.
@techreport{Thil12ab,
title = {Einsatz von N-Tupel-Systemen mit TD-Learning für strategische Brettspiele am Beispiel von Vier Gewinnt},
author = {Markus Thill},
url = {http://www.gm.fh-koeln.de/ciopwebpub/Thil12a.d/Thill12a.pdf},
issn = {2191-365X},
year = {2012},
date = {2012-01-01},
number = {01/12},
address = {Cologne University of Applied Science, Faculty of Computer Science and Engineering Science},
institution = {Research Center CIOP (Computational Intelligence, Optimization and Data Mining)},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
Thill, Markus; Koch, Patrick; Konen, Wolfgang
Reinforcement learning with n-tuples on the game Connect-4 Proceedings Article
In: Coello, Carlos A. Coello; Cutello, Vincenzo (Hrsg.): PPSN'2012: 12th International Conference on Parallel Problem Solving From Nature, Taormina, S. 184–194, Springer, Heidelberg, 2012.
@inproceedings{Thil12b,
title = {Reinforcement learning with n-tuples on the game Connect-4},
author = {Markus Thill and Patrick Koch and Wolfgang Konen},
editor = {Carlos A. Coello Coello and Vincenzo Cutello},
url = {http://maanvs03.gm.fh-koeln.de/webpub/CIOPReports.d/Thi12.d/Thil12.pdf},
year = {2012},
date = {2012-01-01},
urldate = {2012-01-01},
booktitle = {PPSN'2012: 12th International Conference on Parallel Problem Solving From Nature, Taormina},
pages = {184--194},
publisher = {Springer},
address = {Heidelberg},
keywords = {Game Learning, GBG, SOMA},
pubstate = {published},
tppubtype = {inproceedings}
}
Zaefferer, Martin
Optimization and Empirical Analysis of an Event Detection Software for Water Quality Monitoring Abschlussarbeit
Cologne University of Applied Sciences, 2012.
@mastersthesis{Zaef12d,
title = {Optimization and Empirical Analysis of an Event Detection Software for Water Quality Monitoring},
author = {Martin Zaefferer},
url = {http://maanvs03.gm.fh-koeln.de/webpub/PublicDocs.d/Zaef12d.d/Zaef12d.pdf},
year = {2012},
date = {2012-01-01},
school = {Cologne University of Applied Sciences},
keywords = {},
pubstate = {published},
tppubtype = {mastersthesis}
}
Zaefferer, Martin; Bartz-Beielstein, Thomas; Friese, Martina; Naujoks, Boris; Flasch, Oliver
MSPOT: Multi-Criteria Sequential Optimization Forschungsbericht
CIplus Nr. TR 2/2012, 2012.
@techreport{Zaef12b,
title = {MSPOT: Multi-Criteria Sequential Optimization},
author = {Martin Zaefferer and Thomas Bartz-Beielstein and Martina Friese and Boris Naujoks and Oliver Flasch},
year = {2012},
date = {2012-01-01},
number = {TR 2/2012},
institution = {CIplus},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
Zaefferer, Martin; Bartz-Beielstein, Thomas; Friese, Martina; Naujoks, Boris; Flasch, Oliver
Multi-Criteria Optimization for Hard Problems under Limited Budgets Proceedings Article
In: Soule, Terry; Auger, Anne; Moore, Jason; Pelta, David; Solnon, Christine; Preuss, Mike; Dorin, Alan; Ong, Yew-Soon; Blum, Christian; Silva, Dario Landa; Neumann, Frank; Yu, Tina; Ekart, Aniko; Browne, Wil; Kovacs, Tim; Wong, Man-Leung; Pizzuti, Clara; Rowe, Jon; Friedrich, Tobias; Squillero, Giovanni; Bredeche, Nicolas; Smith, Stephen; Motsinger-Rei, Alison; Lozano, Jose; Pelikan, Martin; Meyer-Nienber, Silja; Igel, Christian; and, Greg Hornby (Hrsg.): GECCO Companion '12: Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference companion, S. 1451–1452, ACM, Philadelphia, Pennsylvania, USA, 2012, ISBN: 978-1-4503-1178-6.
@inproceedings{Zaef12a,
title = {Multi-Criteria Optimization for Hard Problems under Limited Budgets},
author = {Martin Zaefferer and Thomas Bartz-Beielstein and Martina Friese and Boris Naujoks and Oliver Flasch},
editor = {Terry Soule and Anne Auger and Jason Moore and David Pelta and Christine Solnon and Mike Preuss and Alan Dorin and Yew-Soon Ong and Christian Blum and Dario Landa Silva and Frank Neumann and Tina Yu and Aniko Ekart and Wil Browne and Tim Kovacs and Man-Leung Wong and Clara Pizzuti and Jon Rowe and Tobias Friedrich and Giovanni Squillero and Nicolas Bredeche and Stephen Smith and Alison Motsinger-Rei and Jose Lozano and Martin Pelikan and Silja Meyer-Nienber and Christian Igel and Greg Hornby and},
isbn = {978-1-4503-1178-6},
year = {2012},
date = {2012-01-01},
booktitle = {GECCO Companion '12: Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference companion},
pages = {1451--1452},
publisher = {ACM},
address = {Philadelphia, Pennsylvania, USA},
abstract = {Many relevant industrial optimization tasks feature more than just one quality criterion. State-of-the-art multi-criteria optimization algorithms require a relatively large number of function evaluations (usually more than 10^5) to approximate Pareto fronts. Due to high cost or time consumption this large amount of function evaluations is not always available. Therefore, it is obvious to combine techniques such as Sequential Parameter Optimization (SPO), which need a very small number of function evaluations only, with techniques from evolutionary multi-criteria optimization (EMO). In this paper, we show how EMO techniques can be efficiently integrated into the framework of the SPO Toolbox (SPOT). We discuss advantages of this approach in comparison to state-of-the-art optimizers. Moreover, with the resulting capability to allow competing objectives, the opportunity arises to not only aim for the best, but also for the most robust solution. Herein we present an approach to optimize not only the quality of the solution, but also its robustness, taking these two goals as objectives for multi-criteria optimization into account.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Many relevant industrial optimization tasks feature more than just one quality criterion. State-of-the-art multi-criteria optimization algorithms require a relatively large number of function evaluations (usually more than 10^5) to approximate Pareto fronts. Due to high cost or time consumption this large amount of function evaluations is not always available. Therefore, it is obvious to combine techniques such as Sequential Parameter Optimization (SPO), which need a very small number of function evaluations only, with techniques from evolutionary multi-criteria optimization (EMO). In this paper, we show how EMO techniques can be efficiently integrated into the framework of the SPO Toolbox (SPOT). We discuss advantages of this approach in comparison to state-of-the-art optimizers. Moreover, with the resulting capability to allow competing objectives, the opportunity arises to not only aim for the best, but also for the most robust solution. Herein we present an approach to optimize not only the quality of the solution, but also its robustness, taking these two goals as objectives for multi-criteria optimization into account.
Bartz-Beielstein, Thomas
Challenging Tasks in Real-World Optimization Buchabschnitt
In: Kacprzyk, Janusz; Pedrycz, Witold (Hrsg.): Handbook of Computational Intelligence, Springer, 2012.
@incollection{Bart12a,
title = {Challenging Tasks in Real-World Optimization},
author = {Thomas Bartz-Beielstein},
editor = {Janusz Kacprzyk and Witold Pedrycz},
year = {2012},
date = {2012-01-01},
booktitle = {Handbook of Computational Intelligence},
publisher = {Springer},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
Bartz-Beielstein, T
Research Topics in Sequential Parameter Optimization Sonstige
Presentation --- ESF Workshop Rome, 2012.
@misc{Bart12g,
title = {Research Topics in Sequential Parameter Optimization},
author = {Bartz-Beielstein, T},
year = {2012},
date = {2012-01-01},
howpublished = {Presentation --- ESF Workshop Rome},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Bartz-Beielstein, Thomas
Spot Seven Sonstige
Presentation---ESF Workshop Rome, 2012.
@misc{Bart12h,
title = {Spot Seven},
author = {Thomas Bartz-Beielstein},
year = {2012},
date = {2012-01-01},
howpublished = {Presentation---ESF Workshop Rome},
keywords = {SPOT},
pubstate = {published},
tppubtype = {misc}
}
Bartz-Beielstein, Thomas; Flasch, Oliver; Zaefferer, Martin
Sequential Parameter Optimization for Symbolic Regression Proceedings Article
In: Gustafson, Steven; Vladislavleva, Ekaterina (Hrsg.): GECCO 2012 Symbolic regression and modeling workshop, S. 495–496, ACM, Philadelphia, Pennsylvania, USA, 2012, ISBN: 978-1-4503-1178-6.
@inproceedings{Flas12b,
title = {Sequential Parameter Optimization for Symbolic Regression},
author = {Thomas Bartz-Beielstein and Oliver Flasch and Martin Zaefferer},
editor = {Steven Gustafson and Ekaterina Vladislavleva},
isbn = {978-1-4503-1178-6},
year = {2012},
date = {2012-01-01},
booktitle = {GECCO 2012 Symbolic regression and modeling workshop},
pages = {495--496},
publisher = {ACM},
address = {Philadelphia, Pennsylvania, USA},
abstract = {Modern Symbolic Regression (SR) engines are complex systems of many components, most of which require some form of parameterization. In this talk, we show how to apply Sequential Parameter Optimization (SPO) as a rigorous method for finding near-optimal parameter settings for SR systems. As modern SR systems often offer alternative operator sets for population initialization, variation, and selection, we also demonstrate how to use modern Design of Experiments (DoE) methods to find problem-specific near-optimal SR system configurations, in addition to near-optimal parameterizations for each selected system component. The experimental design for SR can somehow be tricky, because of interactions in the parameter settings. Methods for handling configurations of parameters which depend on higher-level parameters will be presented. Our exposition is based on a simple framework for statistical sound, reproducible empirical research in SR.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Modern Symbolic Regression (SR) engines are complex systems of many components, most of which require some form of parameterization. In this talk, we show how to apply Sequential Parameter Optimization (SPO) as a rigorous method for finding near-optimal parameter settings for SR systems. As modern SR systems often offer alternative operator sets for population initialization, variation, and selection, we also demonstrate how to use modern Design of Experiments (DoE) methods to find problem-specific near-optimal SR system configurations, in addition to near-optimal parameterizations for each selected system component. The experimental design for SR can somehow be tricky, because of interactions in the parameter settings. Methods for handling configurations of parameters which depend on higher-level parameters will be presented. Our exposition is based on a simple framework for statistical sound, reproducible empirical research in SR.
Bartz-Beielstein, Thomas; Friese, Martina; Naujoks, Boris; Zaefferer, Martin
SPOT Applied to Non-Stochastic Optimization Problems---An Experimental Study Proceedings Article
In: Rodriguez, Katya; Blum, Christian (Hrsg.): GECCO 2012 Late breaking abstracts workshop, S. 645–646, ACM, Philadelphia, Pennsylvania, USA, 2012, ISBN: 978-1-4503-1178-6.
@inproceedings{Bart12d,
title = {SPOT Applied to Non-Stochastic Optimization Problems---An Experimental Study},
author = {Thomas Bartz-Beielstein and Martina Friese and Boris Naujoks and Martin Zaefferer},
editor = {Katya Rodriguez and Christian Blum},
isbn = {978-1-4503-1178-6},
year = {2012},
date = {2012-01-01},
booktitle = {GECCO 2012 Late breaking abstracts workshop},
pages = {645--646},
publisher = {ACM},
address = {Philadelphia, Pennsylvania, USA},
keywords = {SPOT},
pubstate = {published},
tppubtype = {inproceedings}
}
Bartz-Beielstein, Thomas; Preuss, Mike; Zaefferer, Martin
Statistical Analysis of Optimization Algorithms with R Proceedings Article
In: Ochoa, Gabriela (Hrsg.): GECCO 2012 Specialized techniques and applications tutorials, S. 1259–1286, ACM, Philadelphia, Pennsylvania, USA, 2012, ISBN: 978-1-4503-1178-6.
@inproceedings{Bart12f,
title = {Statistical Analysis of Optimization Algorithms with R},
author = {Thomas Bartz-Beielstein and Mike Preuss and Martin Zaefferer},
editor = {Gabriela Ochoa},
isbn = {978-1-4503-1178-6},
year = {2012},
date = {2012-01-01},
booktitle = {GECCO 2012 Specialized techniques and applications tutorials},
pages = {1259--1286},
publisher = {ACM},
address = {Philadelphia, Pennsylvania, USA},
abstract = {Based on experiences from several (rather theoretical) tutorials and workshops devoted to the experimental analysis of algorithms at the world's leading conferences in the field of Computational Intelligence, a practical, hands-on tutorial for the statistical analysis of optimization algorithms is presented. This tutorial -demonstrates how to analyze results from real experimental studies, e.g., experimental studies in EC -item gives a comprehensive introduction in the R language -item introduces the powerful GUI rstudio (http://rstudio.org) -exemplifies the analysis using SPOT (http://cran.r-project.org/web/packages/SPOT/) R is the most attractive and fastest growing open source computer language for statistical computing and graphics in the world. It provides a wide variety of statistical and graphical techniques: linear and nonlinear modeling, statistical tests, time series analysis, classification, clustering, etc. R is distributed over CRAN (http://cran.r-project.org), which is a network of ftp and web servers around the world that store identical, up-to-date, versions of code and documentation for R.},
keywords = {optimization},
pubstate = {published},
tppubtype = {inproceedings}
}
Based on experiences from several (rather theoretical) tutorials and workshops devoted to the experimental analysis of algorithms at the world's leading conferences in the field of Computational Intelligence, a practical, hands-on tutorial for the statistical analysis of optimization algorithms is presented. This tutorial -demonstrates how to analyze results from real experimental studies, e.g., experimental studies in EC -item gives a comprehensive introduction in the R language -item introduces the powerful GUI rstudio (http://rstudio.org) -exemplifies the analysis using SPOT (http://cran.r-project.org/web/packages/SPOT/) R is the most attractive and fastest growing open source computer language for statistical computing and graphics in the world. It provides a wide variety of statistical and graphical techniques: linear and nonlinear modeling, statistical tests, time series analysis, classification, clustering, etc. R is distributed over CRAN (http://cran.r-project.org), which is a network of ftp and web servers around the world that store identical, up-to-date, versions of code and documentation for R.
Bartz-Beielstein, Thomas; Zaefferer, Martin
A Gentle Introduction to Sequential Parameter Optimization Forschungsbericht
CIplus Nr. TR 01/2012, 2012.
@techreport{Bart12i,
title = {A Gentle Introduction to Sequential Parameter Optimization},
author = {Thomas Bartz-Beielstein and Martin Zaefferer},
year = {2012},
date = {2012-01-01},
number = {TR 01/2012},
institution = {CIplus},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
2011
Bartz-Beielstein, Thomas; Friese, Martina; Zaefferer, Martin; Naujoks, Boris; Flasch, Oliver; Konen, Wolfgang; Koch, Patrick
Noisy optimization with sequential parameter optimization and optimal computational budget allocation Proceedings Article
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.
@inproceedings{Bart11b,
title = {Noisy optimization with sequential parameter optimization and optimal computational budget allocation},
author = {Bartz-Beielstein, Thomas and Friese, Martina and Zaefferer, Martin and Naujoks, Boris and Flasch, Oliver and Konen, Wolfgang and Koch, Patrick},
url = {http://doi.acm.org/10.1145/2001858.2001926},
isbn = {978-1-4503-0690-4},
year = {2011},
date = {2011-01-01},
booktitle = {Proceedings of the 13th annual conference companion on Genetic and evolutionary computation},
pages = {119--120},
publisher = {ACM},
address = {Dublin, Ireland},
series = {GECCO '11},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Flasch, Oliver; Bartz-Beielstein, Thomas; 1, Daniel Bicker; Kantschik, Wolfgang; von Strachwitz, Christian
Results of the GECCO 2011 Industrial Challenge: Optimizing Foreign Exchange Trading Strategies Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Scienceand Engineering Science, Nr. 10/11, 2011, ISSN: 2191-365X.
@techreport{Flas11ab,
title = {Results of the GECCO 2011 Industrial Challenge: Optimizing Foreign Exchange Trading Strategies},
author = {Oliver Flasch and Thomas Bartz-Beielstein and Daniel Bicker 1 and Wolfgang Kantschik and Christian von Strachwitz},
url = {http://maanvs03.gm.fh-koeln.de/webpub/CIOPReports.d/Flas11a.d/Flas11a.pdf},
issn = {2191-365X},
year = {2011},
date = {2011-01-01},
number = {10/11},
address = {Cologne University of Applied Science, Faculty of Computer Scienceand Engineering Science},
institution = {Research Center CIOP (Computational Intelligence, Optimization and Data Mining)},
keywords = {GeCCO, optimization},
pubstate = {published},
tppubtype = {techreport}
}
Friese, Martina; Zaefferer, Martin; Bartz-Beielstein, Thomas; Flasch, Oliver; Koch, Patrick; Konen, Wolfgang; Naujoks, Boris
Ensemble Based Optimization and Tuning Algorithms Proceedings Article
In: Hoffmann, F.; Hüllermeier, E. (Hrsg.): Proceedings 21. Workshop Computational Intelligence, S. 119–134, Universitätsverlag Karlsruhe, 2011.
@inproceedings{Frie11ab,
title = {Ensemble Based Optimization and Tuning Algorithms},
author = {Martina Friese and Martin Zaefferer and Thomas Bartz-Beielstein and Oliver Flasch and Patrick Koch and Wolfgang Konen and Boris Naujoks},
editor = {F. Hoffmann and E. Hüllermeier},
year = {2011},
date = {2011-01-01},
booktitle = {Proceedings 21. Workshop Computational Intelligence},
pages = {119--134},
publisher = {Universitätsverlag Karlsruhe},
keywords = {optimization},
pubstate = {published},
tppubtype = {inproceedings}
}
Friese, Martina; Zaefferer, Martin; Thomasand Flasch Bartz-Beielstein, Oliver; Koch, Patrick; Konen, Wolfgang; Naujoks, Boris
Ensemble Based Optimization and Tuning Algorithms Proceedings Article
In: Hoffmann, Frank; Hüllermeier, Eyke (Hrsg.): Proceedings 21. Workshop Computational Intelligence, S. 119–134, Universitätsverlag Karlsruhe, 2011.
@inproceedings{Frie11a,
title = {Ensemble Based Optimization and Tuning Algorithms},
author = {Friese, Martina and Zaefferer, Martin and Bartz-Beielstein, Thomasand Flasch, Oliver and Koch, Patrick and Konen, Wolfgang and Naujoks, Boris},
editor = {Hoffmann, Frank and Hüllermeier, Eyke},
year = {2011},
date = {2011-01-01},
booktitle = {Proceedings 21. Workshop Computational Intelligence},
pages = {119--134},
publisher = {Universitätsverlag Karlsruhe},
keywords = {TDMR},
pubstate = {published},
tppubtype = {inproceedings}
}
Koch, Patrick; Bischl, Bernd; Flasch, Oliver; Bartz-Beielstein, Thomas; Konen, Wolfgang
On the Tuning and Evolution of Support Vector Kernels Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Scienceand Engineering Science, Nr. 04/11, 2011, ISSN: 2191-365X.
@techreport{Koch11ab,
title = {On the Tuning and Evolution of Support Vector Kernels},
author = {Patrick Koch and Bernd Bischl and Oliver Flasch and Thomas Bartz-Beielstein and Wolfgang Konen},
url = {http://maanvs03.gm.fh-koeln.de/webpub/CIOPReports.d/Koch11a.d/svmTuning.pdf},
issn = {2191-365X},
year = {2011},
date = {2011-01-01},
number = {04/11},
address = {Cologne University of Applied Science, Faculty of Computer Scienceand Engineering Science},
institution = {Research Center CIOP (Computational Intelligence, Optimization and Data Mining)},
keywords = {SOMA, TDMR},
pubstate = {published},
tppubtype = {techreport}
}
Koch, Patrick; Bischl, Bernd; Flasch, Oliver; Bartz-Beielstein, Thomas; Konen, Wolfgang
On the Tuning and Evolution of Support Vector Kernels Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Scienceand Engineering Science, Nr. 04/11, 2011, ISSN: 2191-365X.
@techreport{Koch11a,
title = {On the Tuning and Evolution of Support Vector Kernels},
author = {Patrick Koch and Bernd Bischl and Oliver Flasch and Thomas Bartz-Beielstein and Wolfgang Konen},
url = {http://maanvs03.gm.fh-koeln.de/webpub/CIOPReports.d/Koch11a.d/svmTuning.pdf},
issn = {2191-365X},
year = {2011},
date = {2011-01-01},
number = {04/11},
address = {Cologne University of Applied Science, Faculty of Computer Scienceand Engineering Science},
institution = {Research Center CIOP (Computational Intelligence, Optimization and Data Mining)},
keywords = {TDMR},
pubstate = {published},
tppubtype = {techreport}
}
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265 Einträge « ‹ 2 von 27
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Engelhardt, Raphael C; Oedingen, Marc; Lange, Moritz; Wiskott, Laurenz; Konen, Wolfgang
Iterative Oblique Decision Trees Deliver Explainable RL Models Artikel
In: Algorithms, Bd. 16, Nr. 6, S. 282, 2023.
@article{Engelhardt2023,
title = {Iterative Oblique Decision Trees Deliver Explainable RL Models},
author = {Raphael C Engelhardt and Marc Oedingen and Moritz Lange and Laurenz Wiskott and Wolfgang Konen},
url = {https://www.mdpi.com/1999-4893/16/6/282},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
journal = {Algorithms},
volume = {16},
number = {6},
pages = {282},
publisher = {MDPI},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
12.
Engelhardt, Raphael C.; Raycheva, Ralitsa; Lange, Moritz; Wiskott, Laurenz; Konen, Wolfgang
Ökolopoly: Case Study on Large Action Spaces in Reinforcement Learning Proceedings Article
In: Nicosia, Giuseppe; Pardalos, Panos; others, (Hrsg.): 9th International Conference on machine Learning, Optimization, and Data Science (LOD2023), 2023.
@inproceedings{Engelhardt2023a,
title = {Ökolopoly: Case Study on Large Action Spaces in Reinforcement Learning},
author = {Raphael C. Engelhardt and Ralitsa Raycheva and Moritz Lange and Laurenz Wiskott and Wolfgang Konen},
editor = {Giuseppe Nicosia and Panos Pardalos and others},
url = {https://www.gm.fh-koeln.de/ciopwebpub/Engelh23a.d/Engelh23a.pdf},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
booktitle = {9th International Conference on machine Learning, Optimization, and Data Science (LOD2023)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
13.
Seven, Meltem
KI-Agenten im Vergleich: Erfolg von Agenten des Ludii General Game Systems in Partien gegen perfekte oder starke Agenten am Beispiel der Spiele Vier Gewinnt, Nim und Othello Abschlussarbeit
TH Köln – University of Applied Sciences, 2023, (Bachelor thesis).
@mastersthesis{Seven2023,
title = {KI-Agenten im Vergleich: Erfolg von Agenten des Ludii General Game Systems in Partien gegen perfekte oder starke Agenten am Beispiel der Spiele Vier Gewinnt, Nim und Othello},
author = {Meltem Seven},
url = {https://www.gm.fh-koeln.de/~konen/research/PaperPDF/BA_Meltem-Seven-final.pdf},
year = {2023},
date = {2023-01-01},
school = {TH Köln – University of Applied Sciences},
note = {Bachelor thesis},
keywords = {},
pubstate = {published},
tppubtype = {mastersthesis}
}
14.
Konen, Wolfgang
The GBG Class Interface Tutorial V2.3: General Board Game Playing and Learning Forschungsbericht
TH Köln 2022.
@techreport{Konen2022,
title = {The GBG Class Interface Tutorial V2.3: General Board Game Playing and Learning},
author = {Wolfgang Konen},
url = {https://www.gm.fh-koeln.de/ciopwebpub/Konen22a.d/TR-GBG.pdf},
year = {2022},
date = {2022-09-01},
institution = {TH Köln},
school = {Research Center CIOP (Computational Intelligence, Optimization and Data Mining)},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
15.
Weitz, Ann
Untersuchung von selbstlernenden Reinforcement Learning Agenten im computergenerierten Spiel Yavalath Abschlussarbeit
TH Köln – University of Applied Sciences, 2022, (Bachelor thesis).
@mastersthesis{Weitz2022b,
title = {Untersuchung von selbstlernenden Reinforcement Learning Agenten im computergenerierten Spiel Yavalath},
author = {Ann Weitz},
url = {https://www.gm.fh-koeln.de/~konen/research/PaperPDF/BA-Weitz-final-2022.pdf},
year = {2022},
date = {2022-05-01},
school = {TH Köln – University of Applied Sciences},
note = {Bachelor thesis},
keywords = {},
pubstate = {published},
tppubtype = {mastersthesis}
}
16.
Weitz, Ann
Entwicklung einer allgemeinen Schnittstelle zwischen Ludii und dem GBG Framework Forschungsbericht
2022, (Praxisprojekt).
@techreport{Weitz2022,
title = {Entwicklung einer allgemeinen Schnittstelle zwischen Ludii und dem GBG Framework},
author = {Ann Weitz},
url = {https://www.gm.fh-koeln.de/~konen/research/PaperPDF/PP-Doku-Weitz-2022-02.pdf},
year = {2022},
date = {2022-02-01},
school = {TH Köln – University of Applied Sciences},
note = {Praxisprojekt},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
17.
Cöln, Julian
KI-Konzepte für das Erlernen nicht-deterministischer Spiele am Beispiel von "EinStein würfelt nicht!" Abschlussarbeit
TH Köln – University of Applied Sciences, 2022, (Bachelor thesis).
@mastersthesis{Coeln2022,
title = {KI-Konzepte für das Erlernen nicht-deterministischer Spiele am Beispiel von "EinStein würfelt nicht!"},
author = {Julian Cöln},
url = {https://www.gm.fh-koeln.de/~konen/research/PaperPDF/BA_Julian_Coeln2021-final.pdf},
year = {2022},
date = {2022-02-01},
school = {TH Köln – University of Applied Sciences},
note = {Bachelor thesis},
keywords = {},
pubstate = {published},
tppubtype = {mastersthesis}
}
18.
Engelhardt, Raphael C.; Lange, Moritz; Wiskott, Laurenz; Konen, Wolfgang
Sample-based Rule Extraction for Explainable Reinforcement Learning Proceedings Article
In: 8th International Conference on machine Learning, Optimization, and Data Science (LOD2022), 2022.
@inproceedings{Engel2022,
title = {Sample-based Rule Extraction for Explainable Reinforcement Learning},
author = {Raphael C. Engelhardt and Moritz Lange and Laurenz Wiskott and Wolfgang Konen},
year = {2022},
date = {2022-01-01},
booktitle = {8th International Conference on machine Learning, Optimization, and Data Science (LOD2022)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
19.
Scheiermann, Johannes; Konen, Wolfgang
AlphaZero-Inspired Game Learning: Faster Training by Using MCTS Only at Test Time Artikel
In: arXiv preprint arXiv:2204.13307, 2022, (Preprint of the IEEE ToG 2022 paper).
@article{Scheier2022arXiv,
title = {AlphaZero-Inspired Game Learning: Faster Training by Using MCTS Only at Test Time},
author = {Johannes Scheiermann and Wolfgang Konen},
url = {https://arxiv.org/abs/2204.13307},
year = {2022},
date = {2022-01-01},
journal = {arXiv preprint arXiv:2204.13307},
note = {Preprint of the IEEE ToG 2022 paper},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
20.
Scheiermann, Johannes; Konen, Wolfgang
AlphaZero-Inspired Game Learning: Faster Training by Using MCTS Only at Test Time Artikel
In: IEEE Transactions on Games, 2022.
@article{Scheier2022,
title = {AlphaZero-Inspired Game Learning: Faster Training by Using MCTS Only at Test Time},
author = {Johannes Scheiermann and Wolfgang Konen},
url = {https://ieeexplore.ieee.org/document/9893320},
doi = {10.1109/TG.2022.3206733},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
journal = {IEEE Transactions on Games},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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