The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
Prisoner’s dilemma game model Based on historical strategy information
Open accessAbstract
In many dilemmas, decisions are determined not by a single factor, but by multiple ones, including memory, reputation, reward and punishment. In recent years, how to design a mechanism to promote cooperation has become a research hot-spot. However, most of the previous studies mainly consider the historical benefits of the game, and pay less attention to the stability of the strategy (the frequency of strategy changes in the length of memory) and the proportion of memory in decision-making. The decision-making process of group evolution involves the influence of memory information on cooperative evolution in multi round games. It makes up for the lack of stability factors and weights in previous studies. Based on the above factors, a new strategy update rule is proposed to study the influence of the stability of historical strategy information on the evolution of cooperation in prisoner’s dilemma game, and the influence of memory weight on cooperation is considered. The stability of the current strategy is measured by the strategy in historical memory (the number of times the strategy in memory is continuous and consistent with the current strategy), which can determine the probability of an individual learning the neighbor strategy next time. Numerical simulation shows that an appropriate increase in the length of historical memory is more conducive to the emergence of cooperation, and the greater the weight of historical strategy information is, the more conducive to promoting cooperation, which shows that historical strategy information is still the main factor in decision-making. This study will help us understand the cooperative evolution of many real systems, such as nature, biology, society and so on, and effectively design reasonable mechanisms to promote cooperation.
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Cited by
Wei, Q., Chen, H., Zou, H., Zhang, H., Liu, S., Zheng, J., Zhang, S., & Hu, L. (2024) · Journal of Assisted Reproduction and Genetics · doi:10.1007/s10815-024-03066-0 · Cited by 16
Metadata
- Authors
- Gou, Z., & Li, Y.
- Venue
- Scientific Reports
- Published
- 2023-01-02
- Volume
- 13
- Issue
- 1
- Pages
- 1-1
- ISSN
- 2045-2322 (ISSN-L)
- OpenAlex
- W4313478500
- Cited by
- 561
- References
- 45
- FWCI
- 244.94
- Type
- journal article
- Language
- en
- Open access
- gold
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