Differential Privacy for Stackelberg Games
Differential Privacy for Stackelberg Games
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DOI：
10.24963/ijcai.2020/481
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发表时间：
2020-02
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影响因子：
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通讯作者：
Ferdinando Fioretto;Lesia Mitridati;P. V. Hentenryck
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文献类型：
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作者：
Ferdinando Fioretto;Lesia Mitridati;P. V. Hentenryck
引入了一种不同私有(DP)机制来保护序贯市场和相互依赖的市场协调过程中交换的信息。这种协调代表了典型的Stackelberg游戏，并依赖于系统代理之间的敏感信息交换。本文的目的是观察到传统的DP机制引入的扰动从根本上改变了基本的优化问题，甚至导致了不可满足的实例。为了弥补这一局限性，本文引入了隐私保护Stackelberg机制(PPSM)，该机制将隐私保护信息的可行性和保真度(即接近最优)的概念强制执行到原始问题目标。PPSM遵循差别隐私的概念，并确保隐私保护协调机制的结果对于每个代理来说都接近最优。基于实际案例的燃气和电力市场基准的实验结果证明了该方法的有效性。这篇论文的完整版本[Fioretto等人，2020b]包含了完整的证据和关于激励应用的额外讨论。
This paper introduces a differentially private (DP) mechanism to protect the information exchanged during the coordination of sequential and interdependent markets. This coordination represents a classic Stackelberg game and relies on the exchange of sensitive information between the system agents. The paper is motivated by the observation that the perturbation introduced by traditional DP mechanisms fundamentally changes the underlying optimization problem and even leads to unsatisfiable instances. To remedy such limitation, the paper introduces the Privacy-Preserving Stackelberg Mechanism (PPSM), a framework that enforces the notions of feasibility and fidelity (i.e. near-optimality) of the privacy-preserving information to the original problem objective. PPSM complies with the notion of differential privacy and ensures that the outcomes of the privacy-preserving coordination mechanism are close-to-optimality for each agent. Experimental results on several gas and electricity market benchmarks based on a real case study demonstrate the effectiveness of the proposed approach. A full version of this paper [Fioretto et al., 2020b] contains complete proofs and additional discussion on the motivating application.