Game design, interactive arts, interactive media are a new emerging inter- and multi-disciplinary fields that combine different disciplines, including computer science, design, art, engineering, psychology, social science, science, and business. Members of the GUII Lab focus on this emerging areas with emphasis on contributions on understanding the user experience, expanding and applying new artificial intelligence algorithms, and engineering new engaging designs.
The lab is currently focusing on different directions that involve exploring the development of new technological, methodological and design advancements towards developing artefacts that promote social impact and change through games. We thus focus on three areas:
Open Player Models: how to model players' process of playing a game and how to make such models transparent, interpretable and explainable for other players to use to reflect and learn from.
AI with Social Intelligence: how to develop AI techniques to assist in both the game development process as well as assisting players in their gaming experience, through recommendation, coaching, training, reflection, or prediction. Our innovation in developing such AI models in such a way that they are socially and emotionally intelligent taking the players' and designers' needs into consideration.
Process Models of Players Experience: how to map, model and visualize the player experience as a process.
Games for Positive Mental Health: exploring the design and development of different types of games and their use to measure and influence users' mental health, in terms of increasing resilience, emotional regulation, coping through social structure and social play.
At any point in time, the lab is engaging with multiple projects led by different lab members. Check our projects and people websites for more information about the work we are currently doing.
The lab is also collaborating with several partners in the industry and academia. The lab has expertise in:
User Experience testing and measurements, using various methods from qualitative to quantitative to mixed methods and using tools including eye tracking, physiological sensors as well as video annotations.
Artificial Intelligence modeling methods, including Bayesian Networks, Hidden Markov Models, Symbolic and logic based methods, Reinforcement methods, and deep learning. We mostly focus on the use of these methods in modeling human behavior using data from games.
Developing and using visualization methods, including D3, Tableau, and building our own.
Game Tools, developing AI tools for game content development.
Game Engines, including Unity and Unreal and location based game technologies.