Search Field

Zeige alle

2020

Konen, Wolfgang; Bagheri, Samineh

Reinforcement Learning for N-Player Games: The Importance of Final Adaptation Inproceedings

Vasile, Bogdan Filipic Massimiliano (Hrsg.): 9th International Conference on Bioinspired Optimisation Methods and Their Applications (BIOMA), Bruxelles, 2020.

Links | BibTeX | Schlagwörter: CI, Game Learning, GBG, general game playing, learning, optimization, Reinforcement learning

Konen, Wolfgang; Bagheri, Samineh

Final Adaptation Reinforcement Learning for N-Player Games Forschungsbericht

Research Center CIOP (Computational Intelligence, Optimization and Data Mining) 2020.

Links | BibTeX | Schlagwörter: CI, Game Learning, GBG, general game playing, learning, optimization, Reinforcement learning

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.

Links | BibTeX | Schlagwörter: CI, Game Learning, GBG, general game playing, learning, optimization, Reinforcement learning

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).

Links | BibTeX | Schlagwörter: AI, BT-MT, Game Learning, GBG, machine learning, Reinforcement learning

Scheiermann, Johannes

AlphaZero-inspirierte KI-Agenten im General Board Game Playing Abschlussarbeit

TH Köln -- University of Applied Sciences, 2020, (Bachelor thesis).

Links | BibTeX | Schlagwörter: AI, BT-MT, Game Learning, GBG, machine learning, Reinforcement learning

2019

Cöln, Julian; Dittmar, Yannick

Untersuchung von KI Agenten im Spiel Othello Forschungsbericht

TH Köln, Institut für Informatik 2019.

Links | BibTeX | Schlagwörter: AI, BT-MT, Game Learning, GBG, machine learning, Reinforcement learning

Konen, Wolfgang

General Board Game Playing for Education and Research in Generic AI Game Learning Inproceedings

Perez, Diego; Mostaghim, Sanaz; Lucas, Simon (Hrsg.): IEEE Conference on Games, London, 2019.

Links | BibTeX | Schlagwörter: CI, Game Learning, GBG, general game playing, learning, optimization, Reinforcement learning

Barsnick, Felix

Implementierung und Untersuchung eines Turniersystems für KI-Agenten in Brettspielen Abschlussarbeit

TH Köln -- University of Applied Sciences, 2019, (Master thesis).

Links | BibTeX | Schlagwörter: BT-MT, Elo, Game Learning, GBG, Glicko, machine learning, Reinforcement learning

2017

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).

Links | BibTeX | Schlagwörter: BT-MT, CI, Game Learning, GBG, learning, optimization, Reinforcement learning

Kutsch, Johannes

KI-Agenten fur das Spiel 2048: Untersuchung von Lernalgorithmen für nichtdeterministische Spiele Abschlussarbeit

TH Köln -- University of Applied Sciences, 2017, (Bachelor thesis).

Links | BibTeX | Schlagwörter: BT-MT, CI, Game Learning, GBG, learning, optimization, Reinforcement learning

2015

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.

Links | BibTeX | Schlagwörter: Game Learning, learning, Reinforcement learning

Bagheri, Samineh; Thill, Markus; Koch, Patrick; Konen, Wolfgang

Online Adaptable Learning Rates for the Game Connect-4 Artikel

IEEE Transactions on Computational Intelligence and AI in Games, (accepted 11/2014) , S. 1, 2015.

Links | BibTeX | Schlagwörter: Game Learning, learning, Reinforcement learning

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).

Links | BibTeX | Schlagwörter: Game Learning, learning, Reinforcement learning

2014

Konen, Wolfgang; Koch, Patrick

Adaptation in Nonlinear Learning Models for Nonstationary Tasks Inproceedings

Filipic, Bogdan (Hrsg.): PPSN'2014: 13th International Conference on Parallel Problem Solving From Nature, Ljubljana, Springer, Heidelberg, 2014.

Links | BibTeX | Schlagwörter: Game Learning, learning, Reinforcement learning

Thill, Markus; Konen, Wolfgang

Connect-4 Game Playing Framework (C4GPF) Sonstige

2014.

Links | BibTeX | Schlagwörter: Game Learning, learning, Reinforcement learning

Bagheri, Samineh; Thill, Markus; Koch, Patrick; Konen, Wolfgang

Online Adaptable Learning Rates for the Game Connect-4 Forschungsbericht

CIplus (TR 03/2014), 2014, (Preprint version of the article in IEEE Transactions on Computational Intelligence and AI in Games, 2015).

Links | BibTeX | Schlagwörter: Game Learning, learning, Reinforcement learning

Thill, Markus; Bagheri, Samineh; Koch, Patrick; Konen, Wolfgang

Temporal Difference Learning with Eligibility Traces for the Game Connect-4 Inproceedings

Preuss, Mike; Rudolph, Günther (Hrsg.): CIG'2014, International Conference on Computational Intelligence in Games, Dortmund, 2014.

Links | BibTeX | Schlagwörter: Game Learning, learning, Reinforcement learning

2009

Konen, Wolfgang; Bartz-Beielstein, Thomas

Reinforcement learning for games: failures and successes Inproceedings

GECCO '09: Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference, S. 2641–2648, ACM, Montreal, Québec, Canada, 2009.

BibTeX | Schlagwörter: games, machine learning, Reinforcement learning

2008

Konen, Wolfgang; Bartz-Beielstein, Thomas

Reinforcement Learning: Insights from Interesting Failures in Parameter Selection Inproceedings

Rudolph, Günter; et al., (Hrsg.): PPSN'2008: 10th International Conference on Parallel Problem Solving From Nature, Dortmund, S. 478–487, Springer, Berlin, 2008.

BibTeX | Schlagwörter: learning, machine learning, Reinforcement learning

 


Search Field

Zeige alle

19 Einträge « 1 von 2 »
1. Konen, Wolfgang; Bagheri, Samineh: Reinforcement Learning for N-Player Games: The Importance of Final Adaptation. In: Vasile, Bogdan Filipic Massimiliano (Hrsg.): 9th International Conference on Bioinspired Optimisation Methods and Their Applications (BIOMA), Bruxelles, 2020. (Typ: Inproceedings | Links | BibTeX)
2. Konen, Wolfgang; Bagheri, Samineh: Final Adaptation Reinforcement Learning for N-Player Games. Research Center CIOP (Computational Intelligence, Optimization and Data Mining) 2020. (Typ: Forschungsbericht | Links | BibTeX)
3. Konen, Wolfgang: The GBG Class Interface Tutorial V2.2: General Board Game Playing and Learning. Research Center CIOP (Computational Intelligence, Optimization and Data Mining) 2020. (Typ: Forschungsbericht | Links | BibTeX)
4. Scheiermann, Johannes: Sind (trainierte) General-Purpose-RL-Agenten im Brettspiel Othello stärker als (untrainierte) General-Game-Playing Agenten?. TH Köln, Institut für Informatik 2020, (Praxisprojekt). (Typ: Forschungsbericht | Links | BibTeX)
5. Scheiermann, Johannes: AlphaZero-inspirierte KI-Agenten im General Board Game Playing. TH Köln -- University of Applied Sciences, 2020, (Bachelor thesis). (Typ: Abschlussarbeit | Links | BibTeX)
6. Cöln, Julian; Dittmar, Yannick: Untersuchung von KI Agenten im Spiel Othello. TH Köln, Institut für Informatik 2019. (Typ: Forschungsbericht | Links | BibTeX)
7. Konen, Wolfgang: General Board Game Playing for Education and Research in Generic AI Game Learning. In: Perez, Diego; Mostaghim, Sanaz; Lucas, Simon (Hrsg.): IEEE Conference on Games, London, 2019. (Typ: Inproceedings | Links | BibTeX)
8. Barsnick, Felix: Implementierung und Untersuchung eines Turniersystems für KI-Agenten in Brettspielen. TH Köln -- University of Applied Sciences, 2019, (Master thesis). (Typ: Abschlussarbeit | Links | BibTeX)
9. Galitzki, Kevin: Selbstlernende Agenten für das skalierbare Spiel Hex: Untersuchung verschiedener KI-Verfahren im GBG-Framework. TH Köln -- University of Applied Sciences, 2017, (Bachelor thesis). (Typ: Abschlussarbeit | Links | BibTeX)
10. Kutsch, Johannes: KI-Agenten fur das Spiel 2048: Untersuchung von Lernalgorithmen für nichtdeterministische Spiele. TH Köln -- University of Applied Sciences, 2017, (Bachelor thesis). (Typ: Abschlussarbeit | Links | BibTeX)
19 Einträge « 1 von 2 »