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
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
Matthias completed his Master's degree in Computer Science at LIACS. In his master's thesis, he examined the effectiveness of various AI methods, including Reinforcement Learning, Monte Carlo Tree Search, and Heuristics, in tackling the PvP board game Tetris Link. His passion for gaming continues to drive his PhD research on Transfer in Reinforcement Learning and Procedural Content Generation.
Associates
People that collaborate with our lab
Marcello A. Gómez-Maureira
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
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).
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2023—Believable Minecraft Settlements by Means of Decentralised Iterative Planning DOI: 10.1109/CoG57401.2023.10333146
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2023—Chatter Generation through Language Models DOI: 10.1109/CoG57401.2023.10333244
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2023—High-accuracy model-based reinforcement learning, a survey. DOI: 10.1007/s10462-022-10335-w