Chaos in social learning with multiple true states |
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Authors: | Aili Fang Lin Wang Jiuhua Zhao Xiaofan Wang |
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Institution: | 1. School of Mathematics and Statistics Science, Ludong University, Yantai 264025, China;2. Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China |
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Abstract: | Most existing social learning models assume that there is only one underlying true state. In this work, we consider a social learning model with multiple true states, in which agents in different groups receive different signal sequences generated by their corresponding underlying true states. Each agent updates his belief by combining his rational self-adjustment based on the external signals he received and the influence of his neighbors according to their communication. We observe chaotic oscillation in the belief evolution, which implies that neither true state could be learnt correctly by calculating the largest Lyapunov exponents and Hurst exponents. |
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Keywords: | Social learning Opinion dynamics Chaos Consensus Multiple true states |
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