集体威慑作为分类问题：投票规则、威慑可信度与升级风险
Collective deterrence as a classification problem: Voting rules, deterrence credibility, and escalation risk
AI总结：
本文研究集体威慑中威慑可信度与升级风险的权衡，通过信号模型构建二分类问题，分析不同投票规则和概率分布对威慑效果的影响。
摘要：
集体拥有威慑技术的威慑联盟需要机构设计来决定在遭遇攻击或事件时的报复时机。这种机构设计通过社会选择函数形式化，引入了威慑可信度与升级风险之间的权衡。本文通过简单的信号模型研究这一权衡，并构建关联的二分类问题，以确定在多种环境中表现良好的机构设计。对于四成员小联盟，我们计算并研究了不同选择函数和报复及误报概率分布相关的经验ROC曲线统计特性。
英文摘要：
Deterrence coalitions that collectively own their deterrence technology, need an institutional design to decide when to retaliate against an attack or incident. This choice of institutional design, formalized through a social choice function, introduces a tradeoff between credible deterrence and escalation risk. We study this tradeoff via a simple signalling model, and use it to construct an associated binary classification problem to determine institutional designs that perform well in a variety of environments. For a small coalition of four members, we compute and study the statistics of the empirical ROC curves associated to a variety of choice functions and probability distributions for retaliation and false positives.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
