Stochastic evolutionary dynamics of trust games with asymmetric parameters
Open accessAbstract
Trusting in others and reciprocating that trust with trustworthy actions are crucial to successful and prosperous societies. The trust game has been widely used to quantitatively study trust and trustworthiness, involving a sequential exchange between an investor and a trustee. Deterministic evolutionary game theory predicts no trust and no trustworthiness, whereas the behavioral experiments with the one-shot anonymous trust game show that people substantially trust and respond trustworthily. To explain these discrepancies, previous works often turn to additional mechanisms, which are borrowed from other games such as the prisoner's dilemma. Although these mechanisms lead to the evolution of trust and trustworthiness to an extent, the optimal or the most common strategy often involves no trustworthiness. In this paper, we study the impact of asymmetric demographic parameters (e.g., different population sizes) on game dynamics of the trust game. We show that, in a weak-mutation limit, stochastic evolutionary dynamics with the asymmetric parameters can lead to the evolution of high trust and high trustworthiness without any additional mechanisms in well-mixed finite populations. Even full trust and near full trustworthiness can be the most common strategies. These results are qualitatively different from those of the previous works. Our results thereby demonstrate rich evolutionary dynamics of the asymmetric trust game.
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Previous studies on enhancing trust are usually carried out in the framework of one-shot interaction.
“Although there were attempts for enhancing the level of trust from different aspects, we notice that these studies are usually carried out in the framework of one-shot interaction, to our knowledge [8, 9, 16, 24, 26].”
From Conditional investment strategy in evolutionary trust games with repeated group interactions (2022) · cites this paper as [26]
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- Authors
- Lim, I. S.
- Affiliations
- Bangor University (GB)
- Corresponding author
- Lim, Ik Soo
- ORCID
- Lim, Ik Soo
- Venue
- Physical review. E
- Publisher
- American Physical Society (APS)
- Published
- 2020-12-22
- Volume
- 102
- Issue
- 6
- Pages
- 062419-062419
- ISSN
- 2470-0045 (ISSN-L)
- 2470-0053
- OpenAlex
- W3094594818
- Cited by
- 12
- References
- 47
- Citations by year
- 2025: 2 · 2024: 3 · 2023: 3 · 2022: 2 · 2021: 2
- FWCI
- 2.34
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Physical review. E (publishedVersion)
- PubMed (publishedVersion)
- Greenwich Academic Literature Archive (University of Greenwich) (acceptedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Social Sciences › Sociology and Political Science › Evolutionary Game Theory and Cooperation
- Social Sciences › Safety Research › Experimental Behavioral Economics Studies
- Social Sciences › Decision Sciences › Management Science and Operations Research › Game Theory and Applications
- Keywords
- trust game, trustworthiness, stochastic evolutionary dynamics, finite population, well-mixed populations, evolution of cooperation
- MeSH terms
- Biological Evolution, Game Theory, Humans, Stochastic Processes, Trust
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