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Derandomizing random walks in undirected graphs using locally fair exploration strategies

机译:使用局部公平探索策略对无向图中的随机游走进行非随机化

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We consider the problem of exploring an anonymous undirected graph using an oblivious robot. The studied exploration strategies are designed so that the next edge in the robot's walk is chosen using only local information, and so that some local equity (fairness) criterion is satisfied for the adjacent undirected edges. Such strategies can be seen as an attempt to derandomize random walks, and are natural counterparts for undirected graphs of the rotor-router model for symmetric directed graphs. The first of the studied strategies, known as Oldest-First, always chooses the neighboring edge for which the most time has elapsed since its last traversal. Unlike in the case of symmetric directed graphs, we show that such a strategy in some cases leads to exponential cover time. We then consider another strategy called Least-Used-First which always uses adjacent edges which have been traversed the smallest number of times. We show that any Least-Used-First exploration covers a graph G = (V, E) of diameter D within time 0{DE), and in the long run traverses all edges of G with the same frequency.
机译:我们考虑使用遗忘型机器人探索匿名无向图的问题。设计研究的探索策略,以便仅使用本地信息选择机器人行走的下一个边缘,并满足相邻无向边缘的一些局部公平性(公平性)标准。这样的策略可以看作是对随机游走进行非随机化的尝试,并且是对称对称图的转子-路由器模型的无向图的自然对应。研究的策略中的第一个称为“最旧优先”,它总是选择自上次遍历以来经过时间最多的相邻边。与对称有向图不同,我们表明在某些情况下,这种策略会导致指数覆盖时间。然后,我们考虑另一种称为“最少使用优先”的策略,该策略始终使用经过最小次数的相邻边。我们表明,任何使用最少的勘探都可以在时间0 {DE)内覆盖直径D的图形G =(V,E),从长远来看,它以相同的频率遍历G的所有边。

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