c4board

+++ Update 10/2020: FutureWorkGBG: Project themes in GBG for students (PDF) +++

(see also: GBG: General Board Games in CIOP )

Games are interesting in computer science concerning the question whether a computer can learn the game strategies just from self-play, without explicitly programming the tactics or performing exhaustive search. This is a branch of artificial intelligence (AI). Many game learning approaches are based on reinforcement learning, namely TD-learning.

In our research group we have studied extensively the game Connect-4 ("Four-in-a-Row"). We were able to develop an agent which learns Connect-4 nearly perfectly just from self-play. Our Java-based Connect-4 Game Playing Framework (C4GPF) is open-source for interested researchers. Read more...

 

In January'2018 we released Gameboard Hex in GBGGBG, the General Board Game playing and learning framework to the research community as another open-source project.

https://github.com/WolfgangKonen/GBG

Read more about GBG ...

The long-term goal of our research group is it to transfer these learning strategies to many other games (dots-and-boxes, go, Poker, checkers, Abalone, Sim, Othello, ...). The project is related to the research field known as General Game Playing (GGP). The aim of GGP is it to develop agents which are able to learn a great variety of games.

 

People

Wolfgang Konen, Markus Thill, Samineh Bagheri, Johannes Kutsch, Kevin Galitzki, Felix Barsnick, Julian Cöln, Yannick Dittmar, Johannes Scheiermann

Publications

2020

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

Scheiermann, Johannes

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

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

Links | BibTeX

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

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

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

2019

Cöln, Julian; Dittmar, Yannick

Untersuchung von KI Agenten im Spiel Othello Forschungsbericht

TH Köln, Institut für Informatik 2019.

Links | BibTeX

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

Barsnick, Felix

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

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

Links | BibTeX

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

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

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

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

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

2014

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

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

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

Thill, Markus; Konen, Wolfgang

Connect-4 Game Playing Framework (C4GPF) Sonstige

2014.

Links | BibTeX

2009

Konen, Wolfgang; Bartz-Beielstein, Thomas

Reinforcement learning for games: failures and successes -- CMA-ES and TDL in comparision Inproceedings

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

Links | BibTeX

2008

Konen, Wolfgang

Reinforcement Learning für Brettspiele: Der Temporal Difference Algorithmus Forschungsbericht

Cologne University of Applied Sciences 2008.

Links | BibTeX

Konen, Wolfgang; Bartz-Beielstein, Thomas

Reinforcement Learning für strategische Brettspiele Forschungsbericht

Cologne University of Applied Sciences 2008.

Links | BibTeX