Actions Speak Louder Than Words: Evidence-Based Trust Level Evaluation in Multi-Agent Systems

Trust assessment in multi-agent systems (MAS) is critical for ensuring reliable decision-making in dynamic, decentralized environments. However, existing methods for evaluating trust are domain-specific, fragmented, and difficult to generalize. To address this, we propose a generic methodology for trust level calculation that can be instantiated based on domain-specific requirements. We apply this methodology in a smart healthcare use case, where trust is assessed for medical data exchanged between smart ambulances and hospital backends. Through systematic experimentation, we evaluate the feasibility and effectiveness of our approach, identifying key challenges that arise when applying such a trust assessment methodology in practice. These insights allow us to analyze fundamental gaps that must be addressed to further advance the formalization of trust assessment methodologies.