Exploiting an Adversary’s Intentions in Graphical Coordination Games
Exploiting an Adversary’s Intentions in Graphical Coordination Games
复制标题
在图形协调游戏中利用对手的意图
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Philip N. Brown
中科院分区：
文献类型：
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作者：
Brandon C. Collins;Philip N. Brown
关于对手意图的信息如何影响最优系统设计？本文在图形协调博弈的背景下解决了这个问题，其中对手可以通过修改代理的收益间接影响代理的行为。我们研究了一种情况，在这种情况下，系统操作员必须在预测未知对手的行动时选择一个图拓扑。设计师可以通过使用安全策略来限制最坏情况下的损失，有效地为意图造成最大伤害的对手做计划。然而，关于对手意图的细粒度信息可能有助于系统操作员微调防御并获得更好的系统性能。在一个简单的对抗行为模型中，本文询问系统操作员通过微调已知对抗意图的防御可以获得多少收益。我们发现，如果对手是弱的，安全策略对任何对手类型都是近似最优的；然而，对于中等强度的对手，安全策略远不是最优的。
How does information regarding an adversary’s intentions affect optimal system design? This paper addresses this question in the context of graphical coordination games where an adversary can indirectly influence the behavior of agents by modifying their payoffs. We study a situation in which a system operator must select a graph topology in anticipation of the action of an unknown adversary. The designer can limit her worst-case losses by playing a security strategy, effectively planning for an adversary which intends maximum harm. However, fine-grained information regarding the adversary’s intention may help the system operator to fine-tune the defenses and obtain better system performance. In a simple model of adversarial behavior, this paper asks how much a system operator can gain by fine-tuning a defense for known adversarial intent. We find that if the adversary is weak, a security strategy is approximately optimal for any adversary type; however, for moderately-strong adversaries, security strategies are far from optimal.