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Collective Tree Exploration

机译:集体树探索

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摘要

An n-node tree has to be explored by k mobile agents (robots), starting at its root. Every edge of the tree must be traversed by at least one robot, and exploration must be completed as fast as possible. Even when the tree is known in advance, scheduling optimal collective exploration turns out to be NP-hard. We investigate the problem of how communication among robots influences the time for exploring unknown trees. To this end, we consider two scenarios. In the first scenario, robots can communicate by writing at the currently visited node previously acquired information, and reading information available at this node. In the second scenario robots are oblivious of one another, and each of them knows only the part of the tree previously explored by itself. We show that this difference of communication capability significantly influences time of collective exploration. Under the first scenario, we construct an exploration algorithm whose running time for any tree is only O(k/log k) larger than the optimal exploration time with full knowledge of the tree, while under the second scenario we prove that every algorithm works in time Ω (k) larger than optimal, for some trees.
机译:从其根开始,k个移动代理(机器人)必须探索n节点树。树的每个边缘必须至少由一个机器人穿过,并且必须尽快完成探索。即使事先知道了该树,调度最优的集体探索仍然是NP难的。我们研究了机器人之间的通信如何影响探索未知树木的时间的问题。为此,我们考虑两种情况。在第一种情况下,机器人可以通过在当前访问的节点上写入先前获取的信息并读取该节点上可用的信息来进行通信。在第二种情况下,机器人相互遗忘,并且每个机器人只知道以前自己探索过的那部分树。我们表明,这种沟通能力的差异极大地影响了集体探索的时间。在第一种情况下,我们构造了一种探索算法,在充分了解该树的情况下,任何树的运行时间仅比最佳探索时间大O(k / log k),而在第二种情况下,我们证明了每种算法都可以在对于某些树木,时间Ω(k)大于最佳值。

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