论文标题
通过交互模拟对XR接口的计算适应
Computational Adaptation of XR Interfaces Through Interaction Simulation
论文作者
论文摘要
已经提出了自适应和智能的用户界面，作为成功扩展现实（XR）系统的关键组成部分。特别是，预测系统可以推断用户，并为他们提供与任务相关的建议或改编。但是，我们认为这种适应性界面应仔细考虑相互作用的总体\ emph {成本}，以更好地解决预测的不确定性。在该职位论文中，我们讨论了一种调整XR接口的计算方法，以改善用户体验和性能。我们的新型模型应用于菜单选择任务，通过考虑认知成本和运动成本来模拟用户交互。与仅根据预测进行适应的贪婪算法相反，我们的模型从整体上说明了适应性的成本和收益，以适应界面并向用户提供最佳建议。
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.
