Adaptive Human–Agent Interaction in Virtual Reality Exhibitions: A Hybrid Intelligence Perspective
Delaram Javdani Rikhtehgar is a PhD student in the Department of Human Media Interaction. (Co)Promotors are prof.dr. D.K.J. Heylen and dr. S. Wang from the Faculty of Electrical Engineering, Mathematics and Computer Science and dr. S. Schlobach from VU University Amsterdam.

What if a virtual museum could notice what catches your attention and adapt the experience to you?
Virtual museums offer new ways to explore art and cultural heritage, but no two visitors experience an exhibition in the same way. We differ in what we know, what interests us, and what we choose to look at. This dissertation explores how artificial guides in virtual museums can respond to these differences—and how this adaptation may shape the visitor’s experience.
The research examines how adaptive museum systems work, how visitor behaviour can be represented, and how behaviours such as looking at paintings or talking with a guide can be used to make the guide more responsive. Through studies in virtual art museums, it investigates what visitors want to know, how they explore artworks, how they interact with conversational guides, and what happens when those guides adapt to their behaviour.
This is a two-way process. The guide observes and responds to the visitor, while the visitor may, in turn, change their behaviour based on the guide’s responses. In this way, both continuously shape the museum experience together.
The dissertation examines this interaction through the lens of hybrid intelligence: the idea that humans and artificial intelligence can complement one another and jointly shape an experience.
Overall, the research asks whether an artificial guide can become more than a general source of information by taking each visitor into account and, in doing so, become an active partner in exploring art.
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