Constructing Junction Tree Agent Organization with Privacy

Yang Xiang (University of Guelph), Abdulrahman Alshememry (King Saud University)

Abstract

Several frameworks for decentralized reasoning assume a junction tree agent organization (JT-org). JT-org construction involves 3 related tasks on existence recognition, construction, and environment re-decomposition, where re-decomposition incurs loss of JT-org linked privacy, including privacy on agent, topology, private and shared variables. We propose a novel algorithm DAER that accomplishes all 3 tasks distributively. For Tasks 1 and 2, DAER incurs no loss of JT-org linked privacy. For Task 3, it incurs significantly less privacy loss than existing JT-org construction methods. Its performance is formally analyzed and empirically evaluated 1 .