Intervention of flocking behavior based on collision avoidance

This paper focuses on intervention of collective behavior of multi-agent systems. Distinct from the classical leader-follower method that guides group based on the inclination of convergence, here by virtue of collision avoidance in flocking behavior, we intervene in collective behavior by adding some obstacles and designing their moving strategies. A model which can be treat as a shepherding process is developed, where the sheep moves according to Boid model, and the shepherd aims to drive all sheep to a desired place. Two strategies with both global and only local information are designed for the shepherd to fulfill the intervention task. Based on Netlogo, we vividly show the shepherding process and prove the efficiency of the obstacle-avoidance method.