  This position paper outlines a new approach to adapting 3D user interface
(UI) layouts given the complex nature of end-user preferences. Current
optimization techniques, which mainly rely on weighted sum methods, can be
inflexible and result in unsatisfactory adaptations. We propose using
multi-objective optimization and interactive preference elicitation to provide
semi-automated, flexible, and effective adaptations of 3D UIs. Our approach is
demonstrated using an example of single-element 3D layout adaptation with
ergonomic objectives. Future work is needed to address questions around the
presentation and selection of optimal solutions, the impact on cognitive load,
and the integration of preference learning. We conclude that, to make adaptive
3D UIs truly effective, we must acknowledge the limitations of our optimization
objectives and techniques and emphasize the importance of user control.
