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Privacy Leakage of Search-Based Multi-Agent Planning Algorithms

机译:基于搜索的多智能经纪规划算法的隐私泄漏

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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 state-of-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.
机译:保留保护多智能经纪人规划(PP-MAP)最近获得了研究社区的注意力,导致了许多PP地图规划者和理论作品。 许多这样的规划人员缺乏强烈的理论担保,以便比较他们的能力w.r.t. 隐私,多功能和实际的指标至关重要。 在这项工作中,我们提出了这样的公制,建立了现有的理论工作。 我们概括并实施方法,以适用于实际规划域,并在标准的基准上提供最先进的PP地图规划者的评估。 评估表明,所提出的隐私泄漏度量能够提供PP地图规划者的比较并揭示重要属性。

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