Fuzzy Hegselmann-Krause Opinion Dynamics with Opinion Leaders

In this paper, from the perspective of opinion dynamics theory, we investigate the intrinsic interaction principles of a group of autonomous agents and develop a fuzzy opinion dynamics model with leaders. First, this paper divides group agents into three subgroups: opinion followers, positive opinion leaders, and negative opinion leaders according to the opinion's update manner and influence. Then, we consider the uncertainty of the agents' opinion gaps and apply the Fuzzy Inference Machine to the effects of the leaders' opinions on a certain follower's opinion. The innovation of this paper is that the weight is distributed from 0 to 1 in accordance with the closeness among the opinion leaders and followers, which is closer to real life. Finally, the simulation results show that the proposed model can effectively explain the opinion interaction and evolution and conforms with the existing theoretical results in the field of opinion dynamics.