Crowd intelligence evolution based on complex network

Abstract

Purpose In recent years, with the increase in computing power, artificial intelligence can gradually be regarded as intelligent agents and interact with humans, this interactive network has become increasingly complex. Therefore, it is necessary to model and analyze this complex interactive network. This paper aims to model and demonstrate the evolution of crowd intelligence using visual complex networks. Design/methodology/approach This paper uses the complex network to model and observe the collaborative evolution behavior and self-organizing system of crowd intelligence. Findings The authors use the complex network to construct the cooperative behavior and self-organizing system in crowd intelligence. Determine the evolution mode of the node by constructing the interactive relationship between nodes and observe the global evolution state through the force layout. Practical implications The simulation results show that the state evolution map can effectively simulate the distribution, interaction and evolution of crowd intelligence through force layout and the intelligent agents’ link mode the authors proposed. Originality/value Based on the complex network, this paper constructs the interactive behavior and organization system in crowd intelligence and visualizes the evolution process.