 The effect of multigame on cooperation in spatial networkZhibin Li, Danyang Jia, Hao Guo, Yini Geng, Chen Shen, Zhen Wang and Xuelong Li Applied Mathematics and Computation, 2019, vol. 351, issue C, 162-167 Abstract: In real world, cooperation among unrelated agents remains to represent one open challenge in many disciplines. In some cases, subjects can even change their social dilemmas to ensure their own benefit. Inspired by this fact, here we propose a multigame (composed of prisoner's dilemma game and snowdrift game) and its coevolution mechanism in networked populations: if a player succeeds to study the strategy of its opponent, it also learns the game type of its opponent. Based on numerous computation simulations, it is unveiled that compared with the setup of multigame, coevolution mechanism can effectively resolve the problem of collective cooperation. While for this observation, it is attributed to the fact that vast majority of players changed their games to snowdrift game (i.e. lower social dilemma), where cooperation-defection bistable state guarantees cooperation clusters. We hope our finding can inspire more studies for resolving the social dilemmas. Keywords: Multigame; Cooperation; Networks; Coevolution (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:351:y:2019:i:c:p:162-167 DOI: 10.1016/j.amc.2018.12.059 Access Statistics for this article Applied Mathematics and Computation is currently edited by Theodore Simos More articles in Applied Mathematics and Computation from Elsevier |
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