图的结点搜索：理论与算法
Searching the Nodes of a Graph: Theory and Algorithms
摘要：
一个或多个搜索器必须捕获隐藏在图的节点中的不可见的逃避者。我们研究这个图搜索问题，我们强调，我们研究了捕获的节点定位逃避者，这比边搜索得到较少的关注。我们表明，在一般的图的节点搜索的问题是容易比边搜索（然而，节点搜索是NP完全的，就像边搜索）。我们专注于内部单调连接（IMC）的节点搜索的树，并表明它本质上是等价的IMC边搜索。对于一般图上的IMC节点搜索，我们提出了一种新的算法：GSST（Guaranteed Search by Spanning Tree），它通过沿着图G的一棵生成树T执行图G的所有清除移动来清除图G。我们证明了GSST的概率完全变量的存在性。我们的实验还表明，GSST可以有效地节点清除大图，只有一个小的运行时间。还提供了GSST的实现，并公开提供。
英文摘要：
One or more searchers must capture an invisible evader hiding in the nodes of a graph. We study this graph search problem; we emphasize that we study the capture of a node-located evader, which has received less attention than edge search. We show that in general graphs the problem of node search is easier than that of edge search (however node search is NP-complete, just like edge search). We concentrate on the internal monotone connected (IMC) node search of trees and show that it is essentially equivalent to IMC edge search. For IMC node search on general graphs we present a new algorithm: GSST (Guaranteed Search by Spanning Tree) which clears the graph G by performing all its clearing moves along a spanning tree T of G. We prove the existence of probabilistically complete variants of GSST. Our experiments also indicate that GSST can efficiently node-clear large graphs given only a small running time. An implementation of GSST is also provided and made publicly available.
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。
