We 🧪 research with 🎮 games!

Here in the 🎮 Game 🧪 Research 👩‍🔬 Lab (GRL/🎮🧪👩‍🔬) we use digital games as a medium for academic research. We consider 🍿 entertainment games and 😐 'serious' games ⚖️ equally 🏆 valuable objects of study, and involve both in our work. The GRL develops novel 🖥 computational and 🎨 design approaches for ➕ creating, 🕹 playing, and 📊 analyzing 🎮 games; and pursue both the application of state-of-the-art 🤖 AI research to games and new insights for AI from games. The GRL is fundamentally 🫂 interdisciplinary and actively pursues 🧑‍🤝‍🧑 collaborations that challenge the current understanding of games. Our research has strong links to HCI, cognitive science, social science, and digital humanities.

The Lab Team

Our group of player characters.
You can find us and our Lab in 🏫 Gorleaus Buildling BM3.33

Mike Preuss

Assistant Professor

Mike is doing research on algorithms in game AI and how to apply them to practical problems, in the games domain and beyond (e.g. engineering, chemical, social media computing). He is involved in pushing AI use into new areas of game research, as with Team AI (human/agent as well as agent/agent cooperation). He is a regular co-organizer of conferences as IEEE CoG (formerly CIG) and an associate editor of the IEEE Transactions on Games.

Matthias Müller-Brockhausen

Lecturer

Matthias's passion for games in science started with his master's thesis on Tetris Link AI and continued through his PhD research on the synergies between Transfer in Reinforcement Learning and Procedural Content Generation.

Giulio Barbero

Lecturer

I moved to the Netherlands in 2014 to start my studies. Now teaching and researching the use of video games and gamification practices for education.

Qianpu Chen

PhD Candidate

Qianpu Chen is doing research on multi-agent systems. Her work explores strategic interaction and decision-making among intelligent agents in environments related to social dilemmas and game-theoretic settings. She also works on computer vision, including research exploring the intersection of artificial intelligence and art.

Associates

People that collaborate with our lab

Marcello A. Gómez-Maureira

Assistant Professor @ UTwente

Researcher and designer, drawn to projects that involve multidisciplinary challenges and the potential to build connections between them. His research interests focus on the interplay between humans and interactive technology.

Alan Kai Hassen

PhD Candidate

Alan is interested in transferring Artificial Intelligence techniques developed for solving games (Go, Chess, Grand Turismo, etc.) to the Chemistry domain. His main research interest lies in Computer-Aided Synthesis Planning (compare: ESR7 @ ai-dd.eu).

Hainan Yu

PhD Candidate @ Luxembourg

Hainan leverages video games and machine learning to gain knowledge about collaboration mechanisms and train people’s collaboration skills.

  • 2023
    Jelmer Prins  (Masters Thesis)
    Deep Reinforcement Learning for Micro Battles in StarCraft 2
    Supervised by Mike Preuss and Marcello A. Gómez-Maureira
  • 2023
    Vincent Prins  (Masters Thesis)
    Dungeons & Firearms: AI-Directing Action Intensity of Procedural Levels
    Supervised by Mike Preuss and Walter Kosters and Matthias Müller-Brockhausen
  • 2023
    Lex Janssens  (Bachelor Thesis)
    Crossy Road AI: How will the chicken cross the road?
    Supervised by Matthias Müller-Brockhausen and Thomas Moerland
  • 2021
    Edith Järv  (Masters Thesis)
    All Work and No Play Makes Jack an Inefficient Employee: a Study on Video Games' Effects on Sustained Attention
    Supervised by Iris Yocarini and Marcello A. Gómez-Maureira
  • 2023
    Believable Minecraft Settlements by Means of Decentralised Iterative Planning 2023 IEEE Conference on Games (CoG); DOI: 10.1109/CoG57401.2023.10333146
    Arthur van der Staaij, Jelmer Prins, Vincent L Prins, Julian Poelsma, Thera Smit, Matthias Müller-Brockhausen, Mike Preuss
  • 2023
    Chatter Generation through Language Models 2023 IEEE Conference on Games (CoG); DOI: 10.1109/CoG57401.2023.10333244
    Matthias Müller-Brockhausen, Giulio Barbero, Mike Preuss
  • 2023
    High-accuracy model-based reinforcement learning, a survey. Artificial Intelligence Review; DOI: 10.1007/s10462-022-10335-w
    Aske Plaat, Walter Kosters, Mike Preuss