Privacy Leakage of Search-Based Multi-Agent Planning Algorithms

Abstract

Privacy-Preserving Multi-Agent Planning (PP-MAP) has recently gained the attention of the research community, resulting in a number of PP-MAP planners and theoretical works. Many such planners lack strong theoretical guarantees, thus in order to compare their abilities w.r.t. privacy, a versatile and practical metric is crucial. In this work, we propose such a metric, building on the existing theoretical work. We generalize and implement the approach in order to be applicable on real planning domains and provide an evaluation of stateof-the-art PP-MAP planners over the standard set of benchmarks. The evaluation shows that the proposed privacy leakage metric is able to provide a comparison of PP-MAP planners and reveal important properties.