Random graph generation is an important tool for studying large complex networks. Despite abundance of random graph models, constructing models with application-driven constraints is poorly understood. In order to advance state-of-the-art in this area, we focus on random graphs without short...

This paper proposes a tractable model that allows us to analyze how agents' perception of relationships with others determines the structures of networks. In our model, agents are endowed with their own multidimensional characteristics and their payoffs depend on the social distance between...