Volume 141, Number 2, January 2023
|Number of page(s)
|Mathematical and interdisciplinary physics
|18 January 2023
Evolutionary dynamics in networked trust games with diverse investment patterns
School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology Shanghai 200093, China
(a) E-mail: firstname.lastname@example.org (corresponding author)
Received: 18 October 2022
Accepted: 9 January 2023
Most previous works study the evolution of trust by commonly assuming that investors adopt a deterministic investment strategy. In this work, we propose a mechanism of diverse investment in the trust game model on social networks, where each investor adopts a probabilistic strategy by considering the trustworthiness level in the local group to decide whether to invest or not. Extensive simulation results suggest that the proposed mechanism inhibits the untrustworthy behavior and limits its spread, thus stabilizing the cooperative cluster of investors and trustworthy trustees. Therefore, the trust level and global wealth are greatly enhanced comparing to the traditional setup with homogeneous investment pattern. The strong investment diversity can even eliminate untrustworthiness completely despite the fact that the severe temptation condition is disadvantageous to the evolution of trust. We also investigate the impact of investment diversity on trust game model embedding in different network structures with different initial conditions, where we observe similarly positive evolutionary outcomes. We hope these observations can provide valuable insights into further exploring the improvement of trust in real life.
© 2023 EPLA
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