2021
Final adaptation reinforcement learning for N-player games Journal Article
In: arXiv preprint arXiv:2111.14375, 2021.
2020
Reinforcement Learning for N-Player Games: The Importance of Final Adaptation Inproceedings
In: Vasile, Massimiliano; Filipic, Bogdan (Hrsg.): 9th International Conference on Bioinspired Optimisation Methods and Their Applications (BIOMA) , Bruxelles. Video (15 min) + slides available at https://youtu.be/OcpX7ITeH9w, 2020.
The GBG Class Interface Tutorial V2.2: General Board Game Playing and Learning Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining), Oct 2020.
Final Adaptation Reinforcement Learning for N-Player Games Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) 2020.
2019
General Board Game Playing for Education and Research in Generic AI Game Learning Inproceedings
In: Perez, Diego; Mostaghim, Sanaz; Lucas, Simon (Hrsg.): IEEE Conference on Games, London, 2019.
The GBG Class Interface Tutorial V2.0: General Board Game Playing and Learning Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) 2019.
Anomaly Detection in Electrocardiogram Readings with Stacked LSTM Networks Inproceedings
In: Barancíková, Petra; Holena, Martin; others, (Hrsg.): Proc. 19th Conference Information Technologies - Applications and Theory (ITAT 2019), 2019, (Best Paper Award).
2017
The GBG Class Interface Tutorial: General Board Game Playing and Learning Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, 2017, (e-print published at http://www.gm.fh-koeln.de/ciopwebpub/Kone17a.d/TR-GBG.pdf).
2016
Online Adaptable Learning Rates for the Game Connect-4 Journal Article
In: IEEE Transactions on Computational Intelligence and AI in Games, 8 (1), S. 33-42, 2016, (accepted 11/2014).
2015
Reinforcement Learning for Board Games: The Temporal Difference Algorithm Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Sciences, 2015.
Reinforcement Learning für Brettspiele: Der Temporal Difference Algorithmus Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, 2015, (Updated version 2015).
2014
Connect-4 Game Playing Framework (C4GPF) Miscellaneous
2014.
Adaptation in Nonlinear Learning Models for Nonstationary Tasks Inproceedings
In: Bartz-Beielstein, T.; Filipic, B. (Hrsg.): PPSN'2014: 13th International Conference on Parallel Problem Solving From Nature, Ljubljana, S. 292–301, Springer, Heidelberg, 2014.
Online Adaptable Learning Rates for the Game Connect-4 Technical Report
CIplus (TR 03/2014), 2014, (Preprint version of the article in IEEE Transactions on Computational Intelligence and AI in Games, 2016).
Temporal Difference Learning with Eligibility Traces for the Game Connect-4 Inproceedings
In: Preuss, Mike; Rudolph, Günther (Hrsg.): CIG'2014, International Conference on Computational Intelligence in Games, Dortmund, S. 84 – 91, 2014.
2012
Reinforcement learning with n-tuples on the game Connect-4 Inproceedings
In: Coello Coello, Carlos; Cutello, Vincenzo; others, (Hrsg.): PPSN'2012: 12th International Conference on Parallel Problem Solving From Nature, Taormina, S. 184–194, Springer, Heidelberg, 2012.
2011
Self-configuration from a Machine-Learning Perspective Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, Faculty of Computer Science and Engineering Science, (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").
2009
Reinforcement learning for games: failures and successes -- CMA-ES and TDL in comparision Inproceedings
In: GECCO '09: Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference, S. 2641–2648, ACM, Montreal, Québec, Canada, 2009.
Evolutionsstrategien und Reinforcement Learning für strategische Brettspiele Technical Report
Cologne University of Applied Sciences 2009.
2008
Reinforcement Learning: Insights from Interesting Failures in Parameter Selection Inproceedings
In: Rudolph, Günter; others, (Hrsg.): PPSN'2008: 10th International Conference on Parallel Problem Solving From Nature, Dortmund, S. 478–487, Springer, Berlin, 2008.
Reinforcement Learning für Brettspiele: Der Temporal Difference Algorithmus Technical Report
Cologne University of Applied Sciences 2008.
Reinforcement Learning für strategische Brettspiele Technical Report
Cologne University of Applied Sciences 2008.
1999
Learning to generalize from single examples in the dynamic link architecture Incollection
In: Hinton, Geoffrey; Seynowski, Terrence J. (Hrsg.): Unsupervised Learning Foundations of Neural Computation, S. 373390, MIT Press, Cambridge, MA, 1999, (Reprint from [Konen, v.d. Malsburg, Neural Computation, 1993]).
On the performance of neuronal matching algorithms Journal Article
In: Neural Networks, 12 , S. 127-134, 1999.
1996
How fast can neuronal algorithms match patterns? Inproceedings
In: von der Malsburg, Christoph; von Seelen, Werner (Hrsg.): International Conference on Artificial Neural Networks (ICANN), North-Holland, 1996.
1994
Learning to generalize from single examples in the dynamic link architecture Incollection
In: Buzsaki, G.; others, (Hrsg.): Temporal Coding in the brain, S. 205220, Springer, New York, 1994, (Reprint from [Konen, v.d. Malsburg, Neural Computation, 1993]).
A fast dynamic link matching algorithm for invariant pattern recognition Journal Article
In: Neural Networks, 7 , S. 1019-1030, 1994.
1993
Neural mechanisms of elastic pattern matching Technical Report
Institut für Neuroinformatik, Ruhr-Universität Bochum Bochum, (IR-INI 93-01), 1993.
Learning to generalize from single examples in the dynamic link architecture Journal Article
In: Neural Computation, 5 , S. 719-735, 1993.
1992
Unsupervised symmetry detection: A network which learns from single examples Inproceedings
In: Aleksander, Igor (Hrsg.): Proceedings of the International Conference on Artificial Neural Networks (ICANN), S. 121125, North-Holland, Amsterdam, 1992.
Suchfeld
Final adaptation reinforcement learning for N-player games Journal Article
In: arXiv preprint arXiv:2111.14375, 2021.
Reinforcement Learning for N-Player Games: The Importance of Final Adaptation Inproceedings
In: Vasile, Massimiliano; Filipic, Bogdan (Hrsg.): 9th International Conference on Bioinspired Optimisation Methods and Their Applications (BIOMA) , Bruxelles. Video (15 min) + slides available at https://youtu.be/OcpX7ITeH9w, 2020.
The GBG Class Interface Tutorial V2.2: General Board Game Playing and Learning Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining), Oct 2020.
Final Adaptation Reinforcement Learning for N-Player Games Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) 2020.
General Board Game Playing for Education and Research in Generic AI Game Learning Inproceedings
In: Perez, Diego; Mostaghim, Sanaz; Lucas, Simon (Hrsg.): IEEE Conference on Games, London, 2019.
The GBG Class Interface Tutorial V2.0: General Board Game Playing and Learning Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) 2019.
Anomaly Detection in Electrocardiogram Readings with Stacked LSTM Networks Inproceedings
In: Barancíková, Petra; Holena, Martin; others, (Hrsg.): Proc. 19th Conference Information Technologies - Applications and Theory (ITAT 2019), 2019, (Best Paper Award).
The GBG Class Interface Tutorial: General Board Game Playing and Learning Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Science, 2017, (e-print published at http://www.gm.fh-koeln.de/ciopwebpub/Kone17a.d/TR-GBG.pdf).
Online Adaptable Learning Rates for the Game Connect-4 Journal Article
In: IEEE Transactions on Computational Intelligence and AI in Games, 8 (1), S. 33-42, 2016, (accepted 11/2014).
Reinforcement Learning for Board Games: The Temporal Difference Algorithm Technical Report
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) Cologne University of Applied Sciences, 2015.
