The Opinion Dynamics and Bounded Confidence model on Flocking movement world

We present and analyze a model of Opinion Dynamics and Bounded Confidence on the Flocking movement world. There are two systems for interaction. The theorem of `Flocking´ limits the agent´s movement around the world and `Bounded Confidence´ chooses the agents to exchange the opinion. Every time step, agent i looks for the agents in its eyeshot and adjusts their opinion based on the algorithm of Bounded Confidence. When the exchange ends, every agent moves itself in a specifically direction according to Flocking theorem. We simulated the opinion formation process using the proposed model, results show the system is more realistic than the classic BC model.