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How to find Nash equilibria with extreme total latency in network congestion games?

机译:如何在网络拥塞游戏中找到纳什均衡,在网络拥塞游戏中的极端延迟?

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We study the complexity of finding extreme pure Nash equilibria in symmetric network congestion games and analyse how it depends on the graph topology and the number of users. In our context best and worst equilibria are those with minimum respectively maximum total latency. We establish that both problems can be solved by a Greedy algorithm with a suitable tie breaking rule on parallel links. On series-parallel graphs finding a worst Nash equilibrium is NP-hard for two or more users while finding a best one is solvable in polynomial time for two users and NP-hard for three or more. Additionally we establish NP-hardness in the strong sense for the problem of finding a worst Nash equilibrium on a general acyclic graph.
机译:我们研究了对称网络拥塞游戏中查找极端纯NASH均衡的复杂性,并分析了它取决于图形拓扑和用户数量。在我们的上下文中,最佳和最差的均衡是最小的总延迟的那些。我们确定这两个问题都可以通过贪婪算法来解决,并在并行链路上具有合适的绑定规则。在串行平行图中,找到最差的纳什均衡是两个或多个用户的NP努力,同时找到最好的用户,在两个用户的多项式时间中可以在多项式时间和NP-Hard中获得三个或更多。此外,我们在强烈的意义上建立了NP的硬度,对于在一般无循环图上找到最糟糕的纳什均衡问题。

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