Author
Listed:
- Min Zhan
(Key Laboratory of Hunan Province for New Retail Virtual Reality Technology, Institute of Big Data and Internet Innovation, Hunan University of Technology and Business, Changsha 410205, P. R. China)
- Haiming Liang
(#x2020;Business School, Sichuan University, Chengdu 610065, P. R. China)
- Can Zhu
(Key Laboratory of Hunan Province for New Retail Virtual Reality Technology, Institute of Big Data and Internet Innovation, Hunan University of Technology and Business, Changsha 410205, P. R. China)
- Yucheng Dong
(#x2020;Business School, Sichuan University, Chengdu 610065, P. R. China)
Abstract
Psychologically, agents always like to consider similar opinions. Moreover, in real opinion dynamics, people’s opinions usually influence their actions. Therefore, inspired by the HK bounded confidence model, and continuous opinions and discrete action model, in this paper, we propose opinions and actions dynamics model under bounded confidence to investigate the evolution of opinions and actions in a group of agents. In this model, it is assumed that agents have continuous opinions and discrete actions for a certain issue. Each agent often can notice the discrete actions of other agents, but cannot acquire their continuous opinions. So, agents always try to estimate other agents’ opinions based on their actions. Then based on the estimation opinions and bounded confidence, agents update their opinions and actions. Simulation experiments analysis shows that more agents keep silence or undecided as the hesitation range increases. Larger bounded confidence value leads to the stronger attracting power of agents. When the opinion distribution widths of agents with an action are smaller than the bounded confidence value, the agents will be completely attracted by the adjacent agents with large opinion distribution widths and show adjacent actions in the final time.
Suggested Citation
Min Zhan & Haiming Liang & Can Zhu & Yucheng Dong, 2021.
"Opinions and Actions Dynamics Under Bounded Confidence,"
International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 20(01), pages 321-340, January.
Handle:
RePEc:wsi:ijitdm:v:20:y:2021:i:01:n:s0219622021500012
DOI: 10.1142/S0219622021500012
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