Coordinated Innovation Center for Computable Modeling in Management Science, Tianjin University of Finance and Economics, Tianjin 300222, China.
Sci Rep. 2017 Jan 23;7:41076. doi: 10.1038/srep41076.
Social reward, as a significant mechanism explaining the evolution of cooperation, has attracted great attention both theoretically and experimentally. In this paper, we study the evolution of cooperation by proposing a reward model in network population, where a third strategy, reward, as an independent yet particular type of cooperation is introduced in 2-person evolutionary games. Specifically, a new kind of role corresponding to reward strategy, reward agents, is defined, which is aimed at increasing the income of cooperators by applying to them a social reward. Results from numerical simulations show that consideration of social reward greatly promotes the evolution of cooperation, which is confirmed for different network topologies and two evolutionary games. Moreover, we explore the microscopic mechanisms for the promotion of cooperation in the three-strategy model. As expected, the reward agents play a vital role in the formation of cooperative clusters, thus resisting the aggression of defectors. Our research might provide valuable insights into further exploring the nature of cooperation in the real world.
社会奖励作为解释合作进化的重要机制,在理论和实验上都引起了极大的关注。在本文中,我们通过在网络群体中提出一种奖励模型来研究合作的进化,其中引入了第三种策略——奖励,作为一种独立但特殊的合作类型。具体来说,我们定义了一种新的对应奖励策略的角色,奖励代理人,旨在通过社会奖励来增加合作者的收入。数值模拟结果表明,考虑社会奖励会极大地促进合作的进化,这在不同的网络拓扑结构和两种进化博弈中都得到了验证。此外,我们还探索了三策略模型中促进合作的微观机制。正如预期的那样,奖励代理人在形成合作群体方面发挥了至关重要的作用,从而抵抗了破坏者的攻击。我们的研究可能为进一步探索现实世界中合作的本质提供有价值的见解。