From IEEE Task Force on Player Satisfaction Modeling

Research Groups

This page presents a list of research groups that use dissimilar approaches for modeling and enhancing player satisfaction in games. Please let us know if your group demonstrates research activity related to PSM.

Group Name	Group Description
	ITU Game AI Group currently consists of 7 faculty members and 5 research students whose research interests cover all aspects of game development including game theory, game design and game artificial intelligence. Player satisfaction modeling (PSM) through qualitative and quantitative approaches constitutes a primary research focus of the group. They are also hosting and administrating the IEEE PSM task force website and wiki.
	SDU Adaptronics, currently run by Henrik Hautop Lund, currently consists of 5 professors, 6 research associates, 3 PhD and many other students. It has been involved in the Playware and Body Games research projects investigating player satisfaction modeling aspects of young children in physical play activities (augmented-reality games). Part of the group has just established a specialized center for gameplay research named Center for Playware.
	University of Alberta's PaSSAGE is a multidisciplinary research project spanning the fields of Computer Science, Psychology, Mythology, and Narratology. By combining the techniques of psychological modeling and profiling with lessons learned from the telling of myths, it aims to create an automated system, which mimics the improvised, attentive, and creative process of interactive storytelling.
	Games & AI group at Maastricht University concentrates on artificial intelligence in classic board games such as Chess and Go, modern board games such as Settlers of Catan and Puerto Rico, and modern computer games such as Role-Playing Games, Strategy Games, and Shooters. Focus is on making AI more effective or more entertaining by using search techniques, machine learning, player modeling, and agent technology. The group consists of four staff members and half-a-dozen postdocs and PhD students.
	Neural Networks Research Group at UT Austin. Our research concentrates on cognitive science, computational neuroscience, and evolutionary computation, including natural language processing, episodic memory, concept and schema learning, the visual cortex, and evolving neural networks in sequential decision tasks such as robotics, game playing, and resource optimization.
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