Exogenous Rewards for Promoting Cooperation in Scale-Free Networks

Abstract

The design of mechanisms that encourage pro-social behaviours in populations of self-regarding agents is recognised as a major theoretical challenge within several areas of social, life and engineering sciences. When interference from external parties is considered, several heuristics have been identified as capable of engineering a desired collective behaviour at a minimal cost. However, these studies neglect the diverse nature of contexts and social structures that characterise real-world populations. Here we analyse the impact of diversity by means of scale-free interaction networks with high and low levels of clustering, and test various interference mechanisms using simulations of agents facing a cooperative dilemma. Our results show that interference on scale-free networks is not trivial and that distinct levels of clustering react differently to each interference mechanism. As such, we argue that no tailored response fits all scale-free networks and present which mechanisms are more efficient at fostering cooperation in both types of networks. Finally, we discuss the pitfalls of considering reckless interference mechanisms.

Cooperation evolves by the payoff-difference-based probabilistic reward

“…The following studies [20][21][22][23][24][25][26][27] have some conditional mechanisms for rewarding cooperators, while such mechanisms are different from the mechanism of this study. In the adaptive rewarding by Szolnoki and Perc [20], players are more inclined to support cooperation by means of additional incentives if defectors are increasing in their group.…”

“…Han et al [25] introduce the classes of interference mechanisms based on the number of cooperators and the neighbourhood cooperation level. In addition to such classes, Cimpeanu et al [26] present the class of interference mechanism based on the connectivity of the node in the network. Chen et al [27] consider the system that a fraction of cooperators is selected randomly and designated as punishers, and they equally share the associated costs, respectively.…”

“…Han et al [25] also study cost-efficient institutional rewarding strategies in square-lattice networks, showing that local properties in neighbourhood play an important role to achieve cost-efficient incentivisation. In addition, Cimpeanu et al [26] study cost-efficient rewarding strategies in the context of heterogenous networks, showing interference in these types of networks is much more difficult than in homogenous networks. Chen et al [27] show how the cost of peer-punishment can be shared in a probabilistic way to improve cooperation.…”

Research on Diffusion Mechanism of Green Innovation of Cloud Manufacturing Enterprises Based on BA Scale-Free Agglomeration Network Game

“…From the perspective of network aggregation, the cooperative behaviour of innovation subjects with high intermediate value at the network level is more likely to appear in the network. From the perspective of individual preference [51], bounded rationality [52] and expectation [53], when the individual cooperation preference is stronger, the degree of decision-making rationality is higher, and the willingness to cooperate is stronger, and all can promote the cooperation of innovation subjects in the network. Increasingly more researchers have discussed the evolutionary law of the cooperative behaviour of innovation subjects in the process of dynamic network evolution.…”

Cost efficiency of institutional incentives for promoting cooperation in finite populations

“…In a stochastic, finite-population context, so far this problem has been investigated primarily using agent-based and numerical simulations [28,31,[49][50][51][52]. Results demonstrate several interesting phenomena, such as the significant influence of the intensity of selection on incentive strategies and optimal costs.…”