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

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conference contribution
posted on 04.11.2021, 15:14 authored by Boya Di, Nick JenningsNick Jennings
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.

Funding

Samsung Electronics R&D Institute UK (SRUK)

History

Published in

Multi-Agent Systems and Agreement Technologies

Pages

299 - 315

Source

17th European Conference on Multi-Agent Systems, EUMAS 2020, and the 7th International Conference on Agreement Technologies, AT 2020

Publisher

Springer

Version

AM (Accepted Manuscript)

Rights holder

© Springer Nature Switzerland AG

Publisher statement

The final authenticated version is available online at https://doi.org/10.1007/978-3-030-66412-1_19.

Acceptance date

07/12/2020

Publication date

2021-01-05

Copyright date

2020

ISBN

9783030664114; 9783030664121

ISSN

0302-9743

eISSN

1611-3349

Book series

Lecture Notes in Computer Science; 12520

Language

en

Editor(s)

Nick Bassiliades; Georgios Chalkiadakis; Dave de Jonge

Location

Thessaloniki, Greece (Virtual)

Event dates

14th September 2020 - 15th September 2020