An Approach to Enhance Convergence Efficiency of Self-propelled Agent System

In this paper, we investigate a weighted self-propelled particles system, wherein each agent’s direction is determined by its spatial neighbors’ directions with exponential weights concerning the neighbor numbers. In order to describe the fact that some agent with more neighbors might have much larger influence on its neighbors, we introduce a scaling exponent of the neighbor number between 0 and ∞. As the exponent increases, i.e., the effect of weight becomes stronger, the network of agents becomes much easier to achieve direction consensus in our simulation. Especially, when the exponent equals to 1, the convergence efficiency is enhanced.