Acceptable costs of minimax regret equilibrium: A Solution to security games with surveillance-driven probabilistic information
Acceptable costs of minimax regret equilibrium: A Solution to security games with surveillance-driven probabilistic information
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DOI：
10.1016/j.eswa.2018.03.066
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发表时间：
2018-10
期刊：
影响因子：
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通讯作者：
Wenjun Ma;Kevin McAreavey;Weiru Liu;Xudong Luo
中科院分区：
文献类型：
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作者：
Wenjun Ma;Kevin McAreavey;Weiru Liu;Xudong Luo
我们将安全游戏的应用从离线巡逻调度扩展到在线监控驱动的资源分配。这个新领域的一个重要特征是攻击者无法观察或可靠地预测防御者的策略。为此，本文引入了一个新的解概念，称为极小极大后悔均衡的可接受代价，它独立于攻击者对防御者的了解。具体地说，我们研究了玩家的决策如何受到后悔情绪和他们对损失的态度的影响，这是通过最小限度后悔的可接受成本原则来形式化的。然后我们分析了我们的解概念的性质，并提出了一个线性规划公式。最后，我们通过理论评估证明了我们的解决方案对于玩家容错度的微小变化是健壮的，并通过实验评估证明了其在在线资源分配中的可行性。
We extend the application of security games from offline patrol scheduling to online surveillance-driven resource allocation. An important characteristic of this new domain is that attackers are unable to observe or reliably predict defenders’ strategies. To this end, in this paper we introduce a new solution concept, calledacceptable costs of minimax regret equilibrium, which is independent of attackers’ knowledge of defenders. Specifically, we study how a player’s decision making can be influenced by the emotion of regret and their attitude towards loss, formalized by theprinciple of acceptable costs of minimax regret. We then analyse properties of our solution concept and propose a linear programming formulation. Finally, we prove that our solution concept is robust with respect to small changes in a player’s degree of loss tolerance by a theoretical evaluation and demonstrate its viability for online resource allocation through an experimental evaluation.