非理想监测下的偏差检测
Deviator Detection under Imperfect Monitoring
摘要：
Grim-trigger策略是在迭代博弈中维持均衡的基本机制：参与者沿着商定的路径合作，一旦一个参与者偏离，其他参与者就会形成联盟，将他降低到他的最小最大水平。触发这种策略的一个前提条件是，偏离的参与者的身份成为其他参与者的共同知识。这在信息结构只允许对所玩的动作或全局状态进行不完全监控的游戏中可能很难或不可能实现。我们研究的问题，合成有限状态的策略，从一个商定的战略配置文件中发挥有限的图形与不同的信息结构的游戏检测偏差。我们表明，问题是不可判定的，在一般情况下，全球的状态不能被监测。另一方面，我们证明了在完美的监测下的全球状态和不完美的监测行动，问题变得可判定的，我们提出了一个有效的合成过程，涵盖了无限重复的游戏与私人监控。
英文摘要：
Grim-trigger strategies are a fundamental mechanism for sustaining equilibria in iterated games: the players cooperate along an agreed path, and as soon as one player deviates, the others form a coalition to play him down to his minmax level. A precondition to triggering such a strategy is that the identity of the deviating player becomes common knowledge among the other players. This can be difficult or impossible to attain in games where the information structure allows only imperfect monitoring of the played actions or of the global state. We study the problem of synthesising finite-state strategies for detecting the deviator from an agreed strategy profile in games played on finite graphs with different information structures. We show that the problem is undecidable in the general case where the global state cannot be monitored. On the other hand, we prove that under perfect monitoring of the global state and imperfect monitoring of actions, the problem becomes decidable, and we present an effective synthesis procedure that covers infinitely repeated games with private monitoring.
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。
