Privacy-preserving dialogues between agents: a contract-based incentive mechanism for distributed meeting scheduling

Meeting scheduling (MS) is a practical task in everyday life that involves independent agents with different calendars and preferences. In this paper, we consider the distributed MS problem where the host exchanges private information with each attendee separately. Since each agent aims to protect its own privacy and attend the meeting at a time slot that it prefers, it is necessary to design a distributed scheduling mechanism where the privacy leakage can be minimized and as many agents are satisfied with the outcome as possible. To achieve this, we propose an intelligent two-layer mechanism based on contract theory where the host motivates each agent to reveal its true preferences by providing different rewards without knowing the costs of each agent to attend the meeting. We first model the privacy leakage by measuring the difference between the revealed information of an agent’s calendar and other agents’ prior beliefs. An optimal control problem is then formulated such that the reward function and privacy leakage level can be jointly designed for each agent. Through theoretical analysis, we show that our proposed mechanism guarantees the incentive compatibility with respect to all agents. Compared to the state of the art, empirical evaluations show that our proposed mechanism achieves lower privacy leakage and higher social welfare within a small number of rounds.