Abstarct: In this thesis, we consider the problem of learning a hidden graph from a family of graphs on n vertices in a model where the only allowed operation is to query whether a set of vertices induces an edge. Our objective is to estimate the minimum number of queries needed to identify a hidden graph. Toward this end, we apply nonadaptive algorithms generally and study family of matchings, family of stars and family of cliques. We further describe some bounds that apply to general graphs.