Computational Adaptation of XR Interfaces Through Interaction Simulation
- URL: http://arxiv.org/abs/2204.09162v1
- Date: Tue, 19 Apr 2022 23:37:07 GMT
- Title: Computational Adaptation of XR Interfaces Through Interaction Simulation
- Authors: Kashyap Todi, Ben Lafreniere, Tanya Jonker
- Abstract summary: We discuss a computational approach to adapt XR interfaces with the goal of improving user experience and performance.
Our novel model, applied to menu selection tasks, simulates user interactions by considering both cognitive and motor costs.
- Score: 4.6193503399184275
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Adaptive and intelligent user interfaces have been proposed as a critical
component of a successful extended reality (XR) system. In particular, a
predictive system can make inferences about a user and provide them with
task-relevant recommendations or adaptations. However, we believe such adaptive
interfaces should carefully consider the overall \emph{cost} of interactions to
better address uncertainty of predictions. In this position paper, we discuss a
computational approach to adapt XR interfaces, with the goal of improving user
experience and performance. Our novel model, applied to menu selection tasks,
simulates user interactions by considering both cognitive and motor costs. In
contrast to greedy algorithms that adapt based on predictions alone, our model
holistically accounts for costs and benefits of adaptations towards adapting
the interface and providing optimal recommendations to the user.
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