Uncertain opinion formation based on the bounded confidence model

Opinion formation is well used to investigate a consensus or several clusters among the opinions of a group of interaction agents. This study proposes several bounded confidence models to discuss the uncertain opinion formation. In the proposed models, the agents' various tolerances (zero-tolerance, partial tolerance and complete tolerance) on the uncertain opinions are firstly identified. Then, the relevant communication regimes are given to determine the confidence set, and the updated opinions are further calculated. Finally, we explore the influences of various types of agents and self-support on the average number of clusters through simulation analysis.