arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2103.16405cs.GT
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在单选覆盖游戏中,无政府状态的无政府代价是脆弱的

The Price of Anarchy is Fragile in Single-Selection Coverage Games

Joshua Seaton, Philip Brown

摘要:

本文考虑覆盖游戏,其中一组代理的任务是确定最高价值的资源子集,在这种情况下,博弈论的方法是已知的,以产生纳什均衡的因素2的最优。我们考虑的情况下,一些代理遭受通信故障,不能观察到其他代理的行动;在这种情况下,最近的工作表明,如果有k>0妥协代理,纳什均衡只能保证在一个因素的k+1的最优。然而,本文表明,这种最坏情况下的保证是脆弱的,在某种意义上,我们精确,我们表明,如果一个问题的情况下有一个非常差的最坏情况下的保证,那么它一定是非常“接近”的问题的情况下,一个最佳的纳什均衡。相反,一个远离最优纳什均衡的实例必然具有相对较好的最坏情况性能保证。为了将这种脆弱性联系起来,我们使用对数线性学习算法进行了模拟,并表明在最坏情况下的平均性能甚至比我们改进的分析保证要好得多。这表明,无政府状态无政府代价的脆弱性可以通过算法加以利用,以弥补在线沟通的失败。

英文摘要:

This paper considers coverage games in which a group of agents are tasked with identifying the highest-value subset of resources; in this context, game-theoretic approaches are known to yield Nash equilibria within a factor of 2 of optimal. We consider the case that some of the agents suffer a communication failure and cannot observe the actions of other agents; in this case, recent work has shown that if there are k>0 compromised agents, Nash equilibria are only guaranteed to be within a factor of k+1 of optimal. However, the present paper shows that this worst-case guarantee is fragile; in a sense which we make precise, we show that if a problem instance has a very poor worst-case guarantee, then it is necessarily very "close" to a problem instance with an optimal Nash equilibrium. Conversely, an instance that is far from one with an optimal Nash equilibrium necessarily has relatively good worst-case performance guarantees. To contextualize this fragility, we perform simulations using the log-linear learning algorithm and show that average performance on worst-case instances is considerably better even than our improved analytical guarantees. This suggests that the fragility of the price of anarchy can be exploited algorithmically to compensate for online communication failures.

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。

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