Chaos in social learning with multiple true states

Aili Fang, Lin Wang, Jiuhua Zhao and Xiaofan Wang

Physica A: Statistical Mechanics and its Applications, 2013, vol. 392, issue 22, 5786-5792

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.

Keywords: Social learning; Opinion dynamics; Chaos; Consensus; Multiple true states (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:392:y:2013:i:22:p:5786-5792

DOI: 10.1016/j.physa.2013.07.042

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