论文标题
定时网络拥塞游戏中的非盲策略
Non-Blind Strategies in Timed Network Congestion Games
论文作者
论文摘要
网络拥堵游戏是一个方便的模型，用于推理网络中的路由问题：代理必须从源到目标顶点，同时避免交通拥堵，这是根据使用相同链接的玩家数量来衡量的。在过去的40年中，网络拥堵游戏已经进行了广泛的研究，而最近考虑了定时限制的扩展。网络拥堵游戏的大多数结果都考虑了盲目的策略：它们是静态的，并且不适合其他玩家选择的策略。我们扩展了[Bertrand等人，动态网络拥堵游戏的最新结果。 FSTTCS'20]到定时的网络拥塞游戏，其中边缘的可用性取决于（离散时间）。我们证明，计算NASH平衡满足总成本的某些限制（尤其是计算最佳和最差的NASH平衡），并在指数空间中可以实现计算社会最优值。如果所有玩家都有相同的源和目标，则可以在多项式空间中计算社会最佳限制。
Network congestion games are a convenient model for reasoning about routing problems in a network: agents have to move from a source to a target vertex while avoiding congestion, measured as a cost depending on the number of players using the same link. Network congestion games have been extensively studied over the last 40 years, while their extension with timing constraints were considered more recently. Most of the results on network congestion games consider blind strategies: they are static, and do not adapt to the strategies selected by the other players. We extend the recent results of [Bertrand et al., Dynamic network congestion games. FSTTCS'20] to timed network congestion games, in which the availability of the edges depend on (discrete) time. We prove that computing Nash equilibria satisfying some constraint on the total cost (and in particular, computing the best and worst Nash equilibria), and computing the social optimum, can be achieved in exponential space. The social optimum can be computed in polynomial space if all players have the same source and target.
