  While Swarm User Interfaces (SUIs) have succeeded in enriching tangible
interaction experiences, their limitations in autonomous action planning have
hindered the potential for personalized and dynamic interaction generation in
tabletop games. Based on the AI-Gadget Kit we developed, this paper explores
how to integrate LLM-driven agents within tabletop games to enable SUIs to
execute complex interaction tasks. After defining the design space of this kit,
we elucidate the method for designing agents that can extend the meta-actions
of SUIs to complex motion planning. Furthermore, we introduce an add-on prompt
method that simplifies the design process for four interaction behaviors and
four interaction relationships in tabletop games. Lastly, we present several
application scenarios that illustrate the potential of AI-Gadget Kit to
construct personalized interaction in SUI tabletop games. We expect to use our
work as a case study to inspire research on multi-agent-driven SUI for other
scenarios with complex interaction tasks.
