Network generation model by rational agent based on centrality

Abstract

Scale-free and small-world networks receive much attention recently, that are revealed to exist in many natural and artificial systems. There have been several studies on how such networks emerge. In this paper, we propose a novel approach to explain the emergence of different network structures through multi-agent network simulation. Each agent, which represents a node, has rationality and edges to be added are chosen based on mutual common consent. An agent tries to increase its own centrality in the network, and it votes so that its centrality is maximized. Depending on the types of centrality measures, different types of network structures are obtained. This model of network evolution explains emergence of a network where many agents participate in creating it: It includes a social network where each person tries to be more central, and traffic network where each region tries to be more accessible.