Cooperation evolves more when players keep the interaction with unknown players

Shun Kurokawa, Xiudeng Zheng and Yi Tao

Applied Mathematics and Computation, 2019, vol. 350, issue C, 209-216

Abstract: The existence of cooperation is mysterious. When a cooperator interacts with a cooperator more likely than a defector meets with a cooperator, the evolution of cooperation is possible. Thus far, some such mechanisms (e.g., direct reciprocity and group selection) have been proposed to explain the evolution of cooperation. A recent study considered the case where players can decide to stop the interaction with the current opponent and search for the next opponent, or to continue to interact with the current opponent. In this case, the situation where a cooperator interacts with a cooperator more likely than a defector meets with a cooperator can be realized and the evolution of cooperation is possible. Here, relevant to this mechanism is information deficiency. It is reasonable to suppose that players do not always know what the opponent players did. In this study, we aim to answer the following three questions: Will it promote the evolution of cooperation that the players keep the interaction with unknown players? Besides, will the absence of information about the opponent influence the evolution of cooperation? In addition, it is not obvious which strategy is more likely to evolve, a strategy who hopes to keep the interaction with unknown players or a strategy who stops the interaction with unknown players. By using a mathematical model, we reveal that the evolution of cooperation is more likely when players hope to keep the interaction with unknown players and that information deficiency disturbs the evolution of cooperation and that hoping to keep the interaction with unknown partners is likely to evolve for some cases and stopping the interaction with unknown partners is likely to evolve for other cases.

Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300318311044
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:350:y:2019:i:c:p:209-216

DOI: 10.1016/j.amc.2018.12.043

Access Statistics for this article

Applied Mathematics and Computation is currently edited by Theodore Simos

More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().