In this paper, we consider the problem of reconstructing a directed graph using path queries. In this query model of learning, a graph is hidden from the learner, and the learner can access information about it with path queries. For a source and destination node, a path query returns whether there is a directed path from the source to the destination node in the hidden graph. In this paper we first give bounds for learning graphs on $n$ vertices and $k$ strongly connected components. We then study the case of bounded degree directed trees and give new algorithms for learning "almost-trees" -- directed trees to which extra edges have been added. We also give some lower bound constructions justifying our approach.

翻译：在本文中, 我们考虑用路径查询来重建方向图的问题。 在这个查询学习模式中, 向学习者隐藏一个图表, 学习者可以通过路径查询来获取关于它的信息。 对于源点和目的地节点, 路径查询返回隐藏图中是否有源点到目的地节点的定向路径。 在本文中, 我们首先给出了学习以美元为顶点和以美元为基点的强烈连接组件的图表的界限 。 然后我们研究受约束的直线树案例, 并给出新的算法来学习“ 接近树 ”, 也就是增加了额外边缘的直线树 。 我们还给出了更小的界限构造来证明我们的方法是正确的 。