  Self-adaptation approaches usually rely on closed-loop controllers that avoid
human intervention from adaptation. While such fully automated approaches have
proven successful in many application domains, there are situations where human
involvement in the adaptation process is beneficial or even necessary. For such
"human-in-the-loop" adaptive systems, two major challenges, namely transparency
and controllability, have to be addressed to include the human in the
self-adaptation loop. Transparency means that relevant context information
about the adaptive systems and its context is represented based on a digital
twin enabling the human an immersive and realistic view. Concerning
controllability, the decision-making and adaptation operations should be
managed in a natural and interactive way. As existing human-in-the-loop
adaptation approaches do not fully cover these aspects, we investigate
alternative human-in-the-loop strategies by using a combination of digital
twins and virtual reality (VR) interfaces. Based on the concept of the digital
twin, we represent a self-adaptive system and its respective context in a
virtual environment. With the help of a VR interface, we support an immersive
and realistic human involvement in the self-adaptation loop by mirroring the
physical entities of the real world to the VR interface. For integrating the
human in the decision-making and adaptation process, we have implemented and
analyzed two different human-in-the-loop strategies in VR: a procedural control
where the human can control the decision making-process and adaptations through
VR interactions (human-controlled) and a declarative control where the human
specifies the goal state and the configuration is delegated to an AI planner
(mixed-initiative). We illustrate and evaluate our approach based on an
autonomic robot system that is accessible and controlled through a VR
interface.
