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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},
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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},
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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},
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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},
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number = {TR 01/2012},
institution = {CIplus},
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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},
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}
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},
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keywords = {GeCCO, optimization},
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}
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},
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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},
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Koch, Patrick; Konen, Wolfgang; Naujoks, Boris; Flasch, Oliver; Friese, Martina; Zaefferer, Martin; Bartz-Beielstein, Thomas
Tuned Data Mining in R Proceedings Article
In: Hoffmann, Frank; Hüllermeier, Eyke (Hrsg.): Proceedings 21. Workshop Computational Intelligence, S. 147–160, Universitätsverlag Karlsruhe, 2011.
@inproceedings{Koch11bb,
title = {Tuned Data Mining in R},
author = {Patrick Koch and Wolfgang Konen and Boris Naujoks and Oliver Flasch and Martina Friese and Martin Zaefferer and Thomas Bartz-Beielstein},
editor = {Frank Hoffmann and Eyke Hüllermeier},
year = {2011},
date = {2011-01-01},
booktitle = {Proceedings 21. Workshop Computational Intelligence},
pages = {147--160},
publisher = {Universitätsverlag Karlsruhe},
keywords = {Data Mining, SOMA, TDMR},
pubstate = {published},
tppubtype = {inproceedings}
}
Konen, Wolfgang
Self-configuration from a Machine-Learning Perspective Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Science and Engineering Science, Nr. 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").
@techreport{Kone11cb,
title = {Self-configuration from a Machine-Learning Perspective},
author = {Wolfgang Konen},
url = {http://www.gm.fh-koeln.de/ciopwebpub/Kone11c.d/Kone11c.pdf},
issn = {2191-365X},
year = {2011},
date = {2011-01-01},
number = {05/11; arXiv: 1105.1951},
address = {Cologne University of Applied Science, Faculty of Computer Science and Engineering Science},
institution = {Research Center CIOP (Computational Intelligence, Optimization and Data Mining)},
note = {e-print published at http://arxiv.org/abs/1105.1951 and Dagstuhl Preprint Archive, Workshop 11181 "Organic Computing -- Design of Self-Organizing Systems"},
keywords = {Gesture Reconginition, TDMR},
pubstate = {published},
tppubtype = {techreport}
}
Konen, Wolfgang
SFA classification with few training data: Improvements with parametric bootstrap Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Science and Engineering Science, Nr. 09/11, 2011, ISSN: 2191-365X.
@techreport{Kone11fb,
title = {SFA classification with few training data: Improvements with parametric bootstrap},
author = {Wolfgang Konen},
url = {http://maanvs03.gm.fh-koeln.de/webpub/CIOPReports.d/Konen11f.d/Konen11f.pdf},
issn = {2191-365X},
year = {2011},
date = {2011-01-01},
number = {09/11},
address = {Cologne University of Applied Science, Faculty of Computer Science and Engineering Science},
institution = {Research Center CIOP (Computational Intelligence, Optimization and Data Mining)},
keywords = {SFA, SOMA},
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}
Konen, Wolfgang
Der SFA-Algorithmus für Klassifikation Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Science and Engineering Science, Nr. 08/11, 2011, ISSN: 2191-365X.
@techreport{Kone11e,
title = {Der SFA-Algorithmus für Klassifikation},
author = {Wolfgang Konen},
url = {http://maanvs03.gm.fh-koeln.de/webpub/CIOPReports.d/Konen11e.d/Konen11e.pdf},
issn = {2191-365X},
year = {2011},
date = {2011-01-01},
number = {08/11},
address = {Cologne University of Applied Science, Faculty of Computer Science and Engineering Science},
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Konen, Wolfgang; Koch, Patrick
The slowness principle: SFA can detect different slow components in nonstationary time series Artikel
In: International Journal of Innovative Computing and Applications (IJICA), Bd. 3, Nr. 1, S. 3–10, 2011.
@article{KonK10bb,
title = {The slowness principle: SFA can detect different slow components in nonstationary time series},
author = {Wolfgang Konen and Patrick Koch},
url = {http://www.gm.fh-koeln.de/~konen/Publikationen/IJICA2010-howslow.pdf},
year = {2011},
date = {2011-01-01},
journal = {International Journal of Innovative Computing and Applications (IJICA)},
volume = {3},
number = {1},
pages = {3--10},
keywords = {SFA, SOMA},
pubstate = {published},
tppubtype = {article}
}
Konen, Wolfgang; Koch, Patrick; Flasch, Oliver; Bartz-Beielstein, Thomas; Friese, Martina; Naujoks, Boris
Tuned Data Mining: A Benchmark Study on Different Tuners Proceedings Article
In: Krasnogor, Natalio (Hrsg.): GECCO '11: Proceedings of the 13th Annual Conference on Genetic andEvolutionary Computation, S. 1995–2002, 2011.
@inproceedings{Kone11db,
title = {Tuned Data Mining: A Benchmark Study on Different Tuners},
author = {Wolfgang Konen and Patrick Koch and Oliver Flasch and Thomas Bartz-Beielstein and Martina Friese and Boris Naujoks},
editor = {Natalio Krasnogor},
year = {2011},
date = {2011-01-01},
booktitle = {GECCO '11: Proceedings of the 13th Annual Conference on Genetic andEvolutionary Computation},
pages = {1995--2002},
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pubstate = {published},
tppubtype = {inproceedings}
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Bartz-Beielstein, Thomas; Friese, Matina
Sequential Parameter Optimization and Optimal Computational Budget Allocation for Noisy Optimization Problems Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Science and Engineering Science, Nr. 02/11, 2011, ISSN: 2191-365X.
@techreport{Bart11a,
title = {Sequential Parameter Optimization and Optimal Computational Budget Allocation for Noisy Optimization Problems},
author = {Thomas Bartz-Beielstein and Matina Friese},
url = {http://maanvs03.gm.fh-koeln.de/webpub/CIOPReports.d/Bart11a.d/Bart11a.pdf},
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year = {2011},
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Bartz-Beielstein, Thomas; Friese, Martina; Flasch, Oliver; Konen, Wolfgang; Koch, Patrick; Naujoks, Boris
Ensemble-Based Modeling Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Science and Engineering Science, Nr. 06/11, 2011, ISSN: 2191-365X.
@techreport{Bart11eb,
title = {Ensemble-Based Modeling},
author = {Thomas Bartz-Beielstein and Martina Friese and Oliver Flasch and Wolfgang Konen and Patrick Koch and Boris Naujoks},
url = {http://maanvs03.gm.fh-koeln.de/webpub/CIOPReports.d/Bart11e.d/Bart11e.pdf},
issn = {2191-365X},
year = {2011},
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pubstate = {published},
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}
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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}
}
12.
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}
}
13.
Meissner, Simon
Untersuchung des Spiel- und Lernerfolgs künstlicher Intelligenzen für ein nichtdeterministisches Spiel mit imperfekten Informationen: Blackjack in der Game-Learning-Umgebung ’General Board Game’ (GBG) Abschlussarbeit
TH Köln – University of Applied Sciences, 2021, (Bachelor thesis).
@mastersthesis{Meissner2021,
title = {Untersuchung des Spiel- und Lernerfolgs künstlicher Intelligenzen für ein nichtdeterministisches Spiel mit imperfekten Informationen: Blackjack in der Game-Learning-Umgebung ’General Board Game’ (GBG)},
author = {Simon Meissner},
url = {https://www.gm.fh-koeln.de/~konen/research/PaperPDF/BA-Meissner-final-2021.pdf},
year = {2021},
date = {2021-12-01},
school = {TH Köln – University of Applied Sciences},
note = {Bachelor thesis},
keywords = {},
pubstate = {published},
tppubtype = {mastersthesis}
}
14.
Zeh, Tim
Untersuchung von allgemeinen KI-Agenten für das Spiel Poker im General Board Games Framework Abschlussarbeit
TH Köln – University of Applied Sciences, 2021, (Master thesis).
@mastersthesis{Zeh2021,
title = {Untersuchung von allgemeinen KI-Agenten für das Spiel Poker im General Board Games Framework},
author = {Tim Zeh},
url = {https://www.gm.fh-koeln.de/~konen/research/PaperPDF/MA_Zeh_final_Poker-GBG-2021.pdf},
year = {2021},
date = {2021-07-01},
school = {TH Köln – University of Applied Sciences},
note = {Master thesis},
keywords = {},
pubstate = {published},
tppubtype = {mastersthesis}
}
15.
Bagheri, Samineh; Reinicke, Ulf; Anders, Denis; Konen, Wolfgang
Surrogate-assisted optimization for augmentation of finite element techniques Artikel
In: Journal of Computational Science, Bd. 54, S. 101427, 2021.
@article{Bagheri2021,
title = {Surrogate-assisted optimization for augmentation of finite element techniques},
author = {Samineh Bagheri and Ulf Reinicke and Denis Anders and Wolfgang Konen},
url = {https://doi.org/10.1016/j.jocs.2021.101427},
year = {2021},
date = {2021-01-01},
journal = {Journal of Computational Science},
volume = {54},
pages = {101427},
publisher = {Elsevier},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
16.
Engelhardt, Raphael C.; Lange, Moritz; Wiskott, Laurenz; Konen, Wolfgang
Shedding light into the black box of reinforcement learning - extended abstract Proceedings Article
In: Hammer, Barbara; Schilling, Malte; Wiskott, Laurenz (Hrsg.): Workshop on Trustworthy AI in the Wild (at: KI 2021 - German Conf. on AI), 2021.
@inproceedings{Engel2021,
title = {Shedding light into the black box of reinforcement learning - extended abstract},
author = {Raphael C. Engelhardt and Moritz Lange and Laurenz Wiskott and Wolfgang Konen},
editor = {Barbara Hammer and Malte Schilling and Laurenz Wiskott},
url = {https://dataninja.nrw/wp-content/uploads/2021/09/1_Engelhardt_SheddingLight_Abstract.pdf},
year = {2021},
date = {2021-01-01},
booktitle = {Workshop on Trustworthy AI in the Wild (at: KI 2021 - German Conf. on AI)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
17.
Konen, Wolfgang; Bagheri, Samineh
Final adaptation reinforcement learning for N-player games Artikel
In: arXiv preprint arXiv:2111.14375, 2021.
@article{Konen2021,
title = {Final adaptation reinforcement learning for N-player games},
author = {Wolfgang Konen and Samineh Bagheri},
url = {https://arxiv.org/abs/2111.14375},
year = {2021},
date = {2021-01-01},
journal = {arXiv preprint arXiv:2111.14375},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
18.
Thill, Markus; Konen, Wolfgang; Wang, Hao; Bäck, Thomas
Temporal convolutional autoencoder for unsupervised anomaly detection in time series Artikel
In: Applied Soft Computing, Bd. 112, S. 107751, 2021.
@article{Thill2021,
title = {Temporal convolutional autoencoder for unsupervised anomaly detection in time series},
author = {Markus Thill and Wolfgang Konen and Hao Wang and Thomas Bäck},
url = {https://doi.org/10.1016/j.asoc.2021.107751},
year = {2021},
date = {2021-01-01},
journal = {Applied Soft Computing},
volume = {112},
pages = {107751},
publisher = {Elsevier},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
19.
Bagheri, Samineh
Self-Adjusting Surrogate-Assisted Optimization Techniques for Expensive Constrained Black Box Problems Promotionsarbeit
Leiden University and TH Köln, 2020, (PhD thesis).
@phdthesis{Bagheri2020,
title = {Self-Adjusting Surrogate-Assisted Optimization Techniques for Expensive Constrained Black Box Problems},
author = {Samineh Bagheri},
year = {2020},
date = {2020-04-01},
institution = {Institut für Informatik},
school = {Leiden University and TH Köln},
note = {PhD thesis},
keywords = {},
pubstate = {published},
tppubtype = {phdthesis}
}
20.
Konen, Wolfgang; Bagheri, Samineh
Final Adaptation Reinforcement Learning for N-Player Games Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) 2020.
@techreport{Konen20b_TRb,
title = {Final Adaptation Reinforcement Learning for N-Player Games},
author = {Wolfgang Konen and Samineh Bagheri},
url = {http://www.gm.fh-koeln.de/ciopwebpub/Konen20b_TR.d/Konen20b_TR.pdf},
year = {2020},
date = {2020-01-01},
institution = {Research Center CIOP (Computational Intelligence, Optimization and Data Mining)},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
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