Secure Multi-Agent Planning Algorithms

Michal Stolba, Jan Tozicka, Antonín Komenda

Abstract: Multi-agent planning (MAP) is often motivated by the preservation of private information. Such motivation is not only natural for multi-agent systems, but is one of the main reasons, why MAP problems cannot be solved centrally. In this paper, we analyze privacy leakage of the most common MAP paradigms. Then, we propose a new class SECMAP of secure MAP algorithms and show how the existing techniques can be modified to fall in the proposed class.