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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}
}
12.
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}
}
13.
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}
}
14.
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}
}
15.
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}
}
16.
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}
}
17.
Konen, Wolfgang; Bagheri, Samineh
Reinforcement Learning for N-Player Games: The Importance of Final Adaptation Proceedings Article
In: Vasile, Bogdan Filipic Massimiliano (Hrsg.): 9th International Conference on Bioinspired Optimisation Methods and Their Applications (BIOMA), Bruxelles, 2020.
@inproceedings{Konen20bc,
title = {Reinforcement Learning for N-Player Games: The Importance of Final Adaptation},
author = {Wolfgang Konen and Samineh Bagheri},
editor = {Bogdan Filipic Massimiliano Vasile},
url = {http://www.gm.fh-koeln.de/ciopwebpub/Konen20b.d/bioma20-TDNTuple.pdf},
year = {2020},
date = {2020-01-01},
booktitle = {9th International Conference on Bioinspired Optimisation Methods and Their Applications (BIOMA)},
address = {Bruxelles},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
18.
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}
}
19.
Konen, Wolfgang
The GBG Class Interface Tutorial V2.2: General Board Game Playing and Learning Forschungsbericht
Research Center CIOP (Computational Intelligence, Optimization and Data Mining) 2020.
@techreport{Konen20d,
title = {The GBG Class Interface Tutorial V2.2: General Board Game Playing and Learning},
author = {Wolfgang Konen},
url = {http://www.gm.fh-koeln.de/ciopwebpub/Konen20d.d/TR-GBG.pdf},
year = {2020},
date = {2020-01-01},
institution = {Research Center CIOP (Computational Intelligence, Optimization and Data Mining)},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
20.
Scheiermann, Johannes
Sind (trainierte) General-Purpose-RL-Agenten im Brettspiel Othello stärker als (untrainierte) General-Game-Playing Agenten? Forschungsbericht
TH Köln, Institut für Informatik 2020, (Praxisprojekt).
@techreport{Scheier2020,
title = {Sind (trainierte) General-Purpose-RL-Agenten im Brettspiel Othello stärker als (untrainierte) General-Game-Playing Agenten?},
author = {Johannes Scheiermann},
url = {http://www.gm.fh-koeln.de/~konen/research/PaperPDF/INF-Prj-Scheiermann-2020-08.pdf},
year = {2020},
date = {2020-01-01},
institution = {TH Köln, Institut für Informatik},
note = {Praxisprojekt},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
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