Search

Previous experience suggests that prior agreement (a mechanism to test how strongly peers are committed to a common goal) and posterior compensation (a way to compensate cooperators by punishing defectors who violate their commitments) together contribute to the flourishing of cooperation. Far less is known, however, how the determination of the optimal threshold for prior agreement in force and the posterior compensation affect collaboration, and the relevance of different strategies. Here, in the context of public goods games and using an evolutionary game theory model, we investigate the evolution of cooperation and the relevance of different strategies by introducing prior agreements and posterior compensation in structured populations. Analytical results show that posterior compensation does not always promote cooperation and that there are sudden increases and decreases in the first-order phase transition. Interestingly, prior agreements without posterior compensation can also effectively restrain defectors, with cooperation abundance remaining at a high level. Furthermore, the threshold of effective agreement has nonlinear effects on cooperation, with cooperation abundance peaking at intermediate thresholds under specific parameters. • The prior agreements and posterior compensation are introduced in network reciprocity. • The model aims to determine the optimal threshold of agreements and the correlation between different strategies. • The effects of posterior compensation and the threshold of agreements in force on the proportion of cooperation are not linear. [ABSTRACT FROM AUTHOR]

Prevalence of cooperation within groups of selfish individuals is puzzling in that it contradicts with the basic premise of natural selection. Grasping the force that fosters and sustains cooperative behaviors is thus of central importance for the understandings of how companies develop and how societies thrive. In this paper, by means of evolutionary game theory, we refresh the strategy updating rule to be matched with a more realistic scenario where individuals choose someone excellent as the role model and improve themselves continuously to narrow the gap. Under the force of role model, individuals adjust their instantaneous strategy with the increment δ in the next continuous M time steps. And a new role model needs to be selected unless its payoff is more than the focal player's. The computer simulation results illustrate that the self-improvement driven by role model facilitate group cooperation significantly, and the slow but persistent self-improvement performs better. Therefore, in order to achieve higher enterprise performance and build a more harmonious society, managers and government officials should spare no effort to encourage people to keep improving themselves to keep up with their role models. • A new strategy updating rule, self-improvement driven by role model updating rule is proposed. • Players make self-improvement according to the persistent choosing reference roles. • The simulation results show that a slow but persistent self-improvemnet enhances cooperation markedly. [ABSTRACT FROM AUTHOR]

Relational diversity can be characterized by heterogeneous distributions of tie strengths in social networks and this diversity is present not only among humans, but throughout the animal world. We account for this observation by analyzing two network datasets from Facebook. We measure the strength of a tie by calculating the extent of overlap of friends between the two individuals. Based on the previous findings in human experiments, we argue that it is very unlikely that players will allocate their investments equally to their neighbors. There is a tendency that players prefer to donate more to their intimate friends. We find that if players preferentially allocate their investments to their good friends, cooperation will be promoted in PDG. We proved that the facilitation of the cooperative strategy relies mostly on the cooperative allies between best friends, resulting in the formation of cooperative clusters which are able to prevail against the defectors even when there is a large cost to cooperate. Moreover, we discover that the effect of relational diversity cannot be analyzed by adopting classical complex networks models, because neither of the artificial networks is able to produce networks with diverse distributions of tie strengths. It is of vital importance to introduce real social networks to study the influence of diverse relations especially when it comes to humans. This research proposes a brand new perspective to understand the influence of social relations on the emergence of cooperation in evolutionary prisoner’s dilemma games. [ABSTRACT FROM AUTHOR]