In traditional studies,updating rule usually plays an important role in the research of opinion formation.In this work, we propose an opinion dynamics model based on Bayesian updating rule.More detailed, each agent has an initial support degree about an issue, after communicating with neighbors, agent changes its opinion upon the average performance of its neighbors.By assuming average support degree of whole population μ, we find that smaller or larger μ brings a bias towards the issue of opinion formation, which just spends limited time steps to reach the global consensus.However, the intermediate value makes consensus become particularly difficult and takes sufficient long time to arrive at a mixed stationary state, this is because population is able to form compact clusters, which then keep dynamic equilibrium with competition.
opinion dynamics cellular neural networks Moore neighborhood uncertain environment Bayesian updating support degree
Xi Zheng Xiaowu Chen Andrew Adamatzky Rehan Sadiq Sankaran Mahadevan Yong Deng
School of Hanhong, Southwest University, Chongqing 400715, China;School of Computer and Information School of Computer Science and Engineering, BeiHang University, Beijing 100083, China University of the West of England, Bristol, BS 16 1QY, United Kingdom School of Engineering, University of British Columbia Okanagan, 3333 University Way, Kelowna, BC, Ca School of Engineering, Vanderbilt University, Nashville, TN 37235, USA School of Computer and Information Science, Southwest University, Chongqing 400715,China;School of A