Formation of Realistic Networks

对于具有经验观察性质的大规模网络是如何形成的，人们显然缺乏理解。我们通过设计和探索网络形成模型的框架来解决这个问题。我们的目标是分析和实证研究，网络创建模型的新方法如何能够成功地结合现实网络的几个普遍特征。在这个方向上的一个特别的重点是从博弈论的假设和理性代理人的相互作用产生的网络创建模型的力量的理解。此外，一个原始的和大量未探索的方向是网络增强的顺序优化模型。

There is an eminent lack of understanding of how large-scale networks with empirically observed properties are formed. We approach this problem by designing and exploring a framework of network formation models. Our goal is to analytically and empirically examine, how new approaches for network creation models can be successful in combining several of the prevalent features of realistic networks. A special focus in this direction is the understanding of the power of network creation models resulting from game- theoretic assumptions and the interplay of rational agents. Moreover, an original and vastly unexplored direction are sequential optimization models for network augmentation.