Conditional punishment is a double-edged sword in promoting cooperation

Evolutionary dynamics in state-feedback public goods games with peer punishment

Public goods game serves as a valuable paradigm for studying the challenges of collective cooperation in human and natural societies. Peer punishment is often considered an effective incentive for promoting cooperation in such contexts. However, previous related studies have mostly ignored the positive feedback effect of collective contributions on individual payoffs. In this work, we explore global and local state-feedback, where the multiplication factor is positively correlated with the frequency of contributors in the entire population or within the game group, respectively. By using replicator dynamics in an infinite well-mixed population, we reveal that state-based feedback plays a crucial role in alleviating the cooperative dilemma by enhancing and sustaining cooperation compared to the feedback-free case. Moreover, when the feedback strength is sufficiently strong or the baseline multiplication factor is sufficiently high, the system with local state-feedback provides full cooperation, hence supporting the "think globally, act locally" principle. Besides, we show that the second-order free-rider problem can be partially mitigated under certain conditions when the state-feedback is employed. Importantly, these results remain robust with respect to variations in punishment cost and fine.

Understanding the role of peer pressure on engineering students' learning behavior: A TPB perspective

Introduction

With the advent of the digital age, the gradually increasing demands of the engineering job market make it inevitable that engineering students face the pressures that arise from academic life with their peers. To address this issue, this study aims to explore the influence of engineering students' peer pressure on learning behavior based on the theory of planned behavior (TPB).

Methods

In addition to attitudes, subjective norms, and perceived behavioral controls inherent in TPB, two new dimensions-gender difference and peer academic ability-were incorporated to construct a framework of the dimensions of peer pressure as affecting engineering students as well as an expanded model of TPB. A questionnaire survey was conducted with 160 college engineering students and a structural equation model (SEM) was used to test the hypotheses.

Results

The result showed that positive peer pressure can increase engineering students' learning intention and thus promote learning behavior. It was also determined that the TPB model can effectively explain the effect of peer pressure on learning behavior, in addition to expanding and reshaping the relationship between the attitudinal dimension in the TPB model.

Discussion

From the results, it is clear that positive attitudes toward learning can trigger positive peer pressure. Good group norms can induce peer pressure through rewards and punishments as a way to motivate students' learning intention and learning behaviors. When peer pressure is perceived, students mobilize positive emotions toward learning. Meanwhile, both male and female engineering students are also significantly motivated by high peer achievement, and high-performing female students motivate their male peers, which leads to higher graduation rates.

Early exclusion leads to cyclical cooperation in repeated group interactions

Explaining the emergence and maintenance of cooperation among selfish individuals from an evolutionary perspective remains a grand challenge in biology, economy and social sciences. Social exclusion is believed to be an answer to this conundrum. However, previously related studies often assume one-shot interactions and ignore how free-riding is identified, which seem to be too idealistic. In this work, we consider repeated interactions where excluders need to pay a monitoring cost to identify free-riders for exclusion and free-riders cannot participate in the following possible game interactions once they are identified and excluded by excluders in the repeated interaction process. We reveal that the introduction of such exclusion can prevent the breakdown of cooperation in repeated group interactions. In particular, we demonstrate that an evolutionary oscillation among cooperators, defectors and excluders can appear in infinitely large populations when early exclusion is implemented. In addition, we find that the population spends most of the time in states where cooperators dominate for early exclusion when stochastic mutation-selection is considered in finite populations. Our results highlight that early exclusion is successful in solving the mentioned enigma of cooperation in repeated group interactions.

Egoistic punishment outcompetes altruistic punishment in the spatial public goods game

The evolution of costly punishment is a puzzle due to cooperators’ second-order free-riding. Previous studies have proposed many solutions mainly focused on reducing the punishment cost or punishing second-order free riders directly or indirectly. We attempt to explain this confusion from the perspective of punishment motivation, which is why the punisher is willing to pay the cost. The answer is that the punisher is egoistic. Egoistic punishment aims to protect punishers’ own cooperative benefits shared by the defectors. In such case, egoistic punishers would pay a cost in punishing defectors and retrieve lost payoffs from defectors. Here, we examined the evolution and performance of egoistic punishment and compared it with typical altruistic punishment using classic peer-punishment and pool-punishment modes. Results showed egoistic punishment can evolve and effectively promote cooperation within a large parameter range, whether in a well-mixed or structured population, or through peer-punishment or pool-punishment modes. This result is also robust to different strategy-updating rules. The evolution under the pool-punishment mechanism is more complicated. The influence of parameters is counter-intuitive because of cycle dominance; namely, the cost is the key factor to control the level of cooperation and the fine determines the ratio of the punishers and cooperators. Compared with altruistic punishment, egoistic punishment can promote cooperation in a lower-fine and higher-cost area, especially in the pool punishment mode, and the egoistic punishers have stronger survivability. Egoistic punishers represent the natural fairness in a social system. Results revealed that focusing on individual equity can significantly promote collective cooperation. This study provides another explanation for the evolution of costly punishment.

Evolution of cooperation under punishment

Punishment has been considered as an effective mechanism for promoting and sustaining cooperation. In most existing models, punishment always comes as a third strategy alongside cooperation and defection, and it is commonly assumed to be executed based on individual decision rules rather than collective decision rules. Differently from previous works, we employ a democratic procedure by which cooperators cast votes independently and simultaneously for whether to impose punishment on defectors, and we establish a relationship between the cooperators' willingness to punish defectors (WTPD) and whether the punishment is inflicted on defectors. The results illustrate that the population can evolve to full cooperation under consensual punishment. It is noteworthy that, compared with autonomous punishment, whether consensual punishment is more in favor of cooperation crucially depends on the minimum number of votes required for punishment execution as well as the cooperators' WTPD. Our findings highlight the importance of collective decision making in the evolution of cooperation and may provide a mathematical framework for explaining the prevalence of democracy in modern societies.

Cooperator-driven and defector-driven punishments: How do they influence cooperation?

Economic studies have shown that there are two types of regulation schemes which can be considered as a vital part of today's global economy: self-regulation enforced by self-regulation organizations to govern industry practices and government regulation which is considered as another scheme to sustain corporate adherence. An outstanding problem of particular interest is to understand quantitatively the role of these regulation schemes in evolutionary dynamics. Typically, punishment usually occurs for enforcement of regulations. Taking into account both types of punishments to influence the regulations, we develop a game model where six evolutionary situations with corresponding combinations of strategies are considered. Furthermore, a semianalytical method is developed to allow us to give accurate estimations of the boundaries between the phases of full defection and nondefection. We find that, associated with the evolutionary dynamics, for an infinite well-mixed population, the mix of both punishments performs better than one punishment alone in promoting public cooperation, but for a networked population the cooperator-driven punishment turns out to be a better choice. We also reveal the monotonic facilitating effects of the synergy effect, punishment fine, and feedback sensitivity on the public cooperation for an infinite well-mixed population. Conversely, for a networked population an optimal intermediate range of feedback sensitivity is needed to best promote punishers' populations. Overall, a networked structure is overall more favorable for punishers and further for public cooperation, because of both network reciprocity and mutualism between punishers and cooperators who do not punish defectors. We provide physical understandings of the observed phenomena, through a detailed statistical analysis of frequencies of different strategies and spatial pattern formations in different evolution situations. These results provide valuable insights into how to select and enforce suitable regulation measures to let public cooperation remain prevalent, which has potential implications not only for self-regulation, but also for other topics in economics and social science.

The evolution of cooperation in spatial public goods game with conditional peer exclusion

Social exclusion can prevent free riders from participating in social activities and deprive them of sharing cooperative benefits, which is an effective mechanism for the evolution of cooperation. However, traditional peer-exclusion strategies are unconditional, and as long as there are defectors in the group, they will pay a cost to exclude the defectors. In reality, one of the reasons for the complexity of these strategies is that individuals may react differently depending on the environment in which they are located. Based on this consideration, we introduce a kind of conditional peer-exclusion strategy in the spatial public goods game model. Specifically, the behavior of conditional exclusion depends on the number of defectors in the group and can be adjusted by a tolerance parameter. Only if the number of defectors in the group exceeds the tolerance threshold, conditional exclusion can be triggered to exclude defectors. We explore the effects of parameters such as tolerance, exclusion cost, and probability of exclusion success on the evolution of cooperation. Simulation results confirmed that conditional exclusion can greatly reduce the threshold values of the synergy factor above which cooperation can emerge. Especially, when the tolerance is low, very small synergy factors can promote the population to achieve a high level of cooperation. Moreover, even if the probability of exclusion success is low, or the unit exclusion cost is relatively high, conditional exclusion is effective in promoting cooperation. These results allow us to better understand the role of exclusion strategies in the emergence of cooperation.

Self-organized interdependence among populations promotes cooperation by means of coevolution

We show that self-organized interdependence promotes the evolution of cooperation in interdependent networks. The evolution of connections between networks occurs according to the following rule: if a player often wins against its opponent (regardless of its strategy), it is allowed to form an external link with the corresponding partner in another network to obtain additional benefit; otherwise, the opportunity to increase its benefit is lost. Through numerical simulation, it is unveiled that cooperation can be significantly promoted due to interdependent network reciprocity. Interestingly, the synchronization of evolutionary processes emerges on both networks, and individuals can take advantage of interdependent network reciprocity when both the strategies and the coevolving times in the two networks are synchronous.

Cost-effective external interference for promoting the evolution of cooperation

The problem of promoting the evolution of cooperative behaviour within populations of self-regarding individuals has been intensively investigated across diverse fields of behavioural, social and computational sciences. In most studies, cooperation is assumed to emerge from the combined actions of participating individuals within the populations, without taking into account the possibility of external interference and how it can be performed in a cost-efficient way. Here, we bridge this gap by studying a cost-efficient interference model based on evolutionary game theory, where an exogenous decision-maker aims to ensure high levels of cooperation from a population of individuals playing the one-shot Prisoner’s Dilemma, at a minimal cost. We derive analytical conditions for which an interference scheme or strategy can guarantee a given level of cooperation while at the same time minimising the total cost of investment (for rewarding cooperative behaviours), and show that the results are highly sensitive to the intensity of selection by interference. Interestingly, we show that a simple class of interference that makes investment decisions based on the population composition can lead to significantly more cost-efficient outcomes than standard institutional incentive strategies, especially in the case of weak selection.

Evolution of cooperation in a hierarchical society with corruption control

Punishment is widely recognized as a potential promoter in sustaining or even enhancing public cooperation, but it meanwhile induces the problem of second-order free-riders. Particularly, recent evidence shows that costly punishment can be maintained if punishers may engage in corruption. However, how to reduce or eliminate incidents of corruption has been the enduring conundrum in human society. As power asymmetries are associated with hierarchies, we investigate how costly punishment affects the evolution of cooperation in the cases without and with corruption control. In the absence of corruption control, altruistic punishers are incapable of punishing corrupt punishers. Corrupt punishment maintains civilian cooperation but undermines the evolution of altruistic punishment. Otherwise, altruistic punishers can enforce symmetrical or asymmetrical punishment on both corrupt punishers and civilian defectors. In this case, both civilian cooperation and altruistic punishment can be promoted. And as an instrument of corruption control, the policy of asymmetrical punishment is more effective in fostering public cooperation and improving social welfare than symmetrical punishment. Moreover, no matter whether corruption control is considered or not, spiteful corruption that non-cooperative punishers penalize defectors is a more effective form for enhancing cooperation compared with bribery. Our work may thus offer an insight into the effects of corruption on public cooperation and the policy of anti-corruption.