In this paper, we study the exact learning problem for weighted graphs, where we are given the vertex set, $V$, of a weighted graph, $G=(V,E,w)$, but we are not given $E$. The problem, which is also known as graph reconstruction, is to determine all the edges of $E$, including their weights, by asking queries about $G$ from an oracle. As we observe, using simple shortest-path length queries is not sufficient, in general, to learn a weighted graph. So we study a number of scenarios where it is possible to learn $G$ using a subquadratic number of composite queries, which combine two or three simple queries.
翻译:本文研究加权图的精确学习问题:给定加权图G=(V,E,w)的顶点集V,但未知边集E。该问题(亦称为图重构)旨在通过向预言机询问关于G的查询,确定E中所有边及其权重。我们观察到,仅使用简单的最短路径长度查询通常不足以学习加权图。因此,我们研究了若干场景,在这些场景中可通过亚二次数量的复合查询(结合两个或三个简单查询)来学习图G。