Cooperation In Public Goods Research Articles

Evolution of cooperation in heterogeneous populations with asymmetric payoff distribution.

The emergence and maintenance of cooperation is a complex and intriguing issue, especially in the context of widespread asymmetries in interactions that arise from individual differences in real-world scenarios. This study investigates how asymmetric payoff distribution affects cooperation in public goods games by considering a population composed of two types of individuals: strong and weak. The asymmetry is reflected in the fact that strong players receive a larger share of the public pool compared to weak players. Our results demonstrate that asymmetric payoff distribution can promote cooperation in well-mixed populations and trigger the co-evolution of cooperation between sub-populations of strong and weak players. In structured populations, however, the effect of asymmetric payoff distribution on cooperation is contingent on the proportion of strong players and the extent of their payoff share, which can either foster or inhibit cooperation. By adjusting the interaction probability between strong and weak players based on their spatial arrangement on lattice networks, we find that moderate interaction probabilities most effectively maintain cooperation. This study provides valuable insights into the dynamics of cooperation under asymmetric conditions, highlighting the complex role of asymmetrical interactions in the evolution of cooperation.

Particle swarm optimization with historical return decay enhances cooperation in public goods games with investment risks

In the realm of spatial public goods games, heterogeneous investment has emerged as a potent mechanism to enhance cooperative behavior. Savvy investors dynamically adjust their investment levels to optimize returns based on environmental conditions and personal circumstances. This study delves into the evolution of cooperation within a spatial public goods game framework, characterized by heterogeneous investment and associated risks, conducted on a square lattice. We introduce the investors (I) with heterogeneous investment, who updates his investment amount according to the current environment of the game and his own historical experience. We introduce a particle swarm optimization algorithm with decaying historical returns to fine-tune the investment levels of investors. Furthermore, a risk mechanism inspired by the ultimatum game is integrated into the model. This paper investigates the impact of the risk threshold θ on cooperative behavior and examines the influence of the risk decay factor α on cooperation. Additionally, it analyzes the investment behavior of investors in scenarios where two types of investors coexist. Finally, this study explores the effects of the historical best payoff decay factor β and the self-learning rate c1 on cooperative behavior. This research contributes to a nuanced understanding of heterogeneous investment behaviors in public goods games under specified risk mechanisms, providing novel insights into the intricate dynamics of cooperation in complex systems.

The relationship of the source of punishment and personality traits with investment and punishment in a public goods game

In this study, we investigated the motivations behind punishing individuals who exploit common resources, a phenomenon crucial for resource preservation. While some researchers suggest punishment stems from concern for the common good, others propose it is driven by anger toward free riders. To probe these motivations, we developed a modified public goods game in which participants had the option to use their own money or the money from the common pool to punish free riders. The analysis included choice behavior, mouse trajectories, and personality traits like anger, empathy, and altruism. According to our results, investments were highest, and punishment was strongest if participants could punish using credits from the common pool, indicating that this is the preferred option to diminish free riding and maintain cooperation in public goods and common good contexts. Also, punishment was highest if the punisher’s own investment was high, and the investment of others was low. Concerning traits, highly altruistic individuals tended to invest more and punish less in general but gave harsher punishments when they did choose to use the common pool punitively. Conversely, trait anger and trait empathy were linked to low investment while trait empathy also tended to be related to lower punishment. Taken together, these findings underscore the role of situational factors and personality traits in fostering cooperative behavior and shaping societal norms around costly punishment.

Cooperation, punishment, and group change in multilevel public goods experiments

Peer punishment is regarded as an important element in sustaining human cooperation for public good provision. Many behavioral experiments have shown that public good provision is higher if cooperation norms can be enforced by peer punishment. These experiments predominantly focus on single-group public goods, in which people have to choose between their private interests and the interests of their group. However, many societal problems comprise multilevel public goods problems, where multiple local groups are nested within a larger global group. We study experimentally how punishment affects cooperation and norms in multilevel public goods games. In our lab experiment, two local groups are nested within a larger global group. Participants have to choose between not contributing, contributing locally, and contributing globally. Local contributions would lead to a fragmented outcome where two separate local public goods are provided, whereas global contributions would lead to a unified global good that benefits all. Moreover, we study whether cooperation and punishment patterns depend on the type of public good participants are initially exposed to: single-group or multilevel. Participants either begin in a single-group public goods game and then shift to a multilevel public goods game or vice versa. We find that punishment is less effective in multilevel public goods games than in single-group public goods games. Punishment only promotes cooperation in multilevel public goods games if people have prior experience with solving single-group public goods games. Our results refine the boundary conditions for the effectiveness of punishment and suggest that ‘starting small’ by first solving single-group public goods problems is helpful for successful multilevel public good provision.

Cooperation and confusion in public goods games: confusion cannot explain contribution patterns

People behave much more cooperatively than predicted by the self-interest hypothesis in social dilemmas such as public goods games. Some studies have suggested that many decision makers cooperate not because of genuine cooperative preferences but because they are confused about the incentive structure of the game—and therefore might not be aware of the dominant strategy. In this research, we experimentally manipulate whether decision makers receive explicit information about which strategies maximize individual income and group income or not. Our data reveal no statistically significant effects of the treatment variation, neither on elicited contribution preferences nor on unconditional contributions and beliefs in a repeated linear public goods game. We conclude that it is unlikely that confusion about optimal strategies explains the widely observed cooperation patterns in social dilemmas such as public goods games.

Collaboration and Competition in Shifting Global Power Dynamics: A Review of China's Next Act: How Sustainability and Technology are Reshaping China's Rise and the World's Future by Scott Moore

Collaboration and Competition in Shifting Global Power DynamicsA Review of China's Next Act: How Sustainability and Technology are Reshaping China's Rise and the World's Future by Scott Moore Jialan Deal (bio) A Review of China's Next Act: How Sustainability and Technology are Reshaping China's Rise and the World's Future by Scott Moore Introduction In an interconnected world, geopolitical and economic competition between rival powers becomes increasingly complex. Although international relations scholars debate whether China deserves the title of superpower, the country's ascendency threatens the current U.S. hegemonic world order. Despite heated rhetoric from both China and the United States, some issues, including climate change and public health crises, transcend differences and destabilize both countries. When addressing these problems, the United States and China must decide whether to respond with cooperation or competition. In his book, China's Next Act: How Sustainability and Technology are Reshaping China's Rise and the World's Future, Scott Moore, director of China Programs and Strategic Initiatives at the University of Pennsylvania, explores the nuances of U.S.-China relations, particularly opportunities for both competition and cooperation between the two countries. The Future of US-China Collaboration In China's Next Act, Moore draws on his extensive knowledge from working at the China desk at the State Department and his experience living in Hong Kong. The book incorporates testimonies from experts in U.S.-China relations and from those with a deep understanding of how China has managed its extraordinary development over the past few decades. Moore explicitly uses the book's final sentence to elucidate his central message: "in a future shaped by climate change, pandemics, and technology, all countries ultimately need China to succeed—and vice versa" (Moore 2022). He believes that it is impossible to ignore China altogether due to China's size and current international standing; however, due to China and the United States' ideological differences, it is also impossible for the two countries to collaborate in all areas. Moore primarily argues the following two points for navigating this complex relationship: first, certain issues such as scientific collaboration and conservation must be protected from politicization for the public good, and second, substate actors must play a larger role in the relationship between the United States and China. The book begins with exploring cooperation and competition in public goods between the United States and China through public health and climate change lenses. It then focuses on the impact of technology on U.S.-China relations and discusses a range of issues, such as talent acquisition, innovation, and emerging technologies. While these topics seem disconnected, they are all issue areas that unite Washington and Beijing in competition or cooperation. Though Moore has a self-acknowledged bias towards liberalism, his arguments are supported by reliable statistics and policy exploration from both the Chinese and American perspectives. Furthermore, he is unafraid to probe into the heart of topics, looking past the surface-level propaganda released by governments. This nuanced [End Page 129] approach is particularly important when he dissects the statistics reported by the Chinese Communist Party (CCP), thus providing a clearer picture of reality in China without the distortion of propaganda. The Politicization of Public Goods Moore spends his first few chapters describing what public goods are and how they present opportunities for interaction between the United States and China. He defines public goods as "things like climate protection, pandemic prevention, and knowledge production that benefit the citizens of all countries, yet typically cannot be provided by one country alone" (Moore 2022, 2). Although an issue that threatens all may seem like an opportunity for global unity, Moore states that many topics have become increasingly politicized, making cooperation impossible. He argues that Beijing's approach to public goods has been increasingly influenced by three illiberal influences: authoritarianism, protectionism, and nationalism. According to him, this change is part of China's struggle to adapt to ecological and technological problems (Moore 2022, 7). Moore points to the U.S. and Chinese response to the COVID-19 pandemic as a prime example. Though scientists shared the virus's genome, allowing for some substate cooperation, nationalism and national agendas...

The evolution of cooperation in spatial public goods games under a risk-transfer mechanism

An interest coalition of sharing benefits and risks, such as cross shareholding between companies, allows them to transfer risks in a competitive business world. In a public goods game, cooperators are at the risk of being exploited by defectors. This paper studies whether such risk-transfer mechanism can induce cooperative behaviors in social dilemmas. We model a public goods game with coalition mechanism in a structured population. The players are categorized by whether they cooperate as well as whether they are willing to form coalitions. Those who are willing (unwilling) to form coalitions with others are called coalitional (traditional) individuals. By exploring the phase transitions of systems, the spatial dynamics of some phases and the evolution of characteristic spatial distributions of strategies, we study the effect of this mechanism on cooperation. The results show that the positive (negative) impact of such interest coalitions on the competitiveness of cooperators (defectors) can be improved as the closeness of interest relationship within coalitions increases. However, this does not mean that a closer coalition can absolutely increase the overall level of cooperation in a more complex four-strategy system. This is related to the transformation from CCs (coalitional cooperators) to TDs (traditional defectors) due to CCs' breaking of the encirclement formed by CDs (coalitional defectors) at a low synergy coefficient, as well as the invasion of TCs (traditional cooperators) to CCs at the boundary separating CCs, TCs and TDs at a high synergy coefficient.

Effect of heterogeneous investment induced by payoff and emotion on cooperation in public goods games by considering memory decline effects.

Payoff, emotion, and historical memory directly determine investment decision-making for incomplete rational men in a public goods game (PGG). How these factors affect investment and cooperation behavior has not been investigated yet. Thus, we proposed a new investment model involving theses three factors to examine its coupling effect on cooperation in PGG. An emotional increment was employed to describe the emotional change in every round by supposing an investor' pleasure to a cooperator but regret to a defector. Furthermore, an emotional index was formed by accumulating these historical changes with a memory decline effect. Then an investment formula was proposed by considering this emotional index and a historical payoff. Moreover, the cooperation level affected by these factors was investigated. Results show a mutually reinforcing relationship between emotional and payoff investments. A poor memory capacity coefficient allows defectors to change their behaviors but produces some opportunists. A large memory length results in a high cooperator fraction but is not suggested to be too large.

Combined effect of pure punishment and reward in the public goods game

The evolution of cooperation in public goods games based on the evolutionary game theory has been widely studied to obtain potential solutions to social dilemmas. In addition, as the main factors of human cooperation, reward and punishment have also been widely studied. In this paper, the manipulators are introduced into the game. It is assumed that manipulators both reward cooperators and punish pure defectors, but do not contribute to the common pool. The evolution of manipulators with cooperators and defectors is analyzed on a square lattice. The results show that the combination of pure punishment and reward is effective in maintaining cooperation. Moreover, for any synergy factor, there is a wide range of parameters that allow for the coexistence of manipulators and cooperators.

Evolution of cooperation in public goods games with dynamic resource allocation: A fairness preference perspective

Exploring the conditions under which cooperation can emerge in populations has long been a subject for humans. Fair preference psychology has been incorporated into the analytical framework of the public goods game. Based on considering the dynamic update of trust-driven investment willingness, we introduce a dynamic payoff allocation mechanism and loners to traditional PGG, explaining how the mechanism related to fairness preferences promotes cooperation. We assume that payoffs are equally allocated among players when the payoffs do not exceed the threshold. Otherwise, the excess portion is proportionally allocated according to the investment willingness of cooperators. The effects of parameter changes on the evolution of cooperation are investigated by conducting Monte Carlo simulations. The results show that introducing dynamic payoff allocation and loners can effectively promote cooperation in a specific range of parameters. Specifically, the existence of loners is a double-edged sword. Loners can prevent players from adopting defection behaviors on a large scale when the payoff of cooperation is unsatisfied and inhibit the emergence and diffusion of cooperative strategies as the payoff of cooperators increases. When the payoff of cooperation is dissatisfactory, the dynamic payoff allocation mechanism can promote the average investment willingness of cooperators to accelerate the spread of cooperation. However, the payoff reallocation coefficient should not be set too high, and a high-level threshold of payoff reallocation may lead to the failure of the dynamic payoff allocation mechanism. There is an optimal payoff reallocation coefficient to maximize the efficiency of the proposed mechanism. Moreover, the optimal payoff reallocation coefficient that can maximize the cooperation level is distinct for the diverse combination of enhancement factor and loss aversion coefficient. However, its value should be set at a low level in general. These results may help researchers better understand the evolution of cooperation in public goods games with dynamic resource allocation from a fairness preference perspective.

State-dependent optimal incentive allocation protocols for cooperation in public goods games on regular networks

Incentives are often used to promote cooperation in a population of competing agents. Furthermore, it is a common method to combine both punishment and reward. However, how to optimally allocate an amount of incentive budget as reward and punishment to enhance cooperation in structured populations is still a challenging task. To address this problem, we here consider evolutionary public goods games on regular networks and assume that a fixed budget of incentives is dynamically allocated to reward cooperators or to punish defectors in a group of players, depending on the actual cooperation level in the population. By means of the pair approximation approach, we derive the dynamical equation for depicting the evolutionary dynamics of cooperation. We then formulate two optimal incentive allocation problems by minimizing the payoff difference between defectors and cooperators and maximizing the gradient of selection, respectively. We theoretically derive the optimal incentive allocation protocols for the two objective functions we considered. We find that the obtained protocols both depend sensitively on the efficiency ratio of reward to punishment. In addition, we provide numerical calculations to verify our theoretical results.

The restart effect in social dilemmas shows humans are self-interested not altruistic

Do economic games show evidence of altruistic or self-interested motivations in humans? A huge body of empirical work has found contrasting results. While many participants routinely make costly decisions that benefit strangers, consistent with the hypothesis that humans exhibit a biologically novel form of altruism (or "prosociality"), many participants also typically learn to pay fewer costs with experience, consistent with self-interested individuals adapting to an unfamiliar environment. Key to resolving this debate is explaining the famous "restart effect," a puzzling enigma whereby failing cooperation in public goods games can be briefly rescued by a surprise restart. Here we replicate this canonical result, often taken as evidence of uniquely human altruism, and show that it 1) disappears when cooperation is invisible, meaning individuals can no longer affect the behavior of their groupmates, consistent with strategically motivated, self-interested, cooperation; and 2) still occurs even when individuals are knowingly grouped with computer players programmed to replicate human decisions, consistent with confusion. These results show that the restart effect can be explained by a mixture of self-interest and irrational beliefs about the game's payoffs, and not altruism. Consequently, our results suggest that public goods games have often been measuring self-interested but confused behaviors and reject the idea that conventional theories of evolution cannot explain the results of economic games.

The evolution of cooperation in public goods games on the scale-free community network under multiple strategy-updating rules

Most social dilemmas have public goods properties, and social networks have scale-free characteristics and community structure features. Meanwhile, due to individuals’ diverse preferences, there are individuals in the network who use different strategy-updating rules. Based on this, this research explores how cooperation evolves in scale-free community networks with public goods games, as well as the influence of multiple strategy-updating rules on cooperation evolution. Pairwise comparison rules and aspiration-driven rules are the two types of strategy-updating rules discussed here. Several simulations are displayed, along with the results of their simulations. We discover that community structure facilitates the emergence of cooperation with public goods games. Meanwhile, the enhancement factor’s value determines the relationship between the proportion of the two updating rules and the cooperation density. There is a negative relationship between the initial ratio of pairwise comparison rules and the cooperation density under a weak enhancement factor. And the initial ratio of pairwise comparison rules and the cooperation density forms a “U”-shaped relationship under a strong enhancement factor. Pairwise comparison rules seem to be more sensitive to the variance in the proportion of the two strategy-updating rules. Our findings might help us better understand the evolution of cooperation in social networks.

Evolution of cooperation in public goods games with segregated networks and periodic invasion

Despite the cost, rational individuals routinely modify their relationships in social networks to optimize their payoffs. To develop this observation, we propose a segregation strategy that impels individuals to sever the adverse ties between defectors and their group at some cost, and then we randomly rewire the link-broken cooperative individuals. Moreover, time-varying environmental factors impact the relationships between interacting individuals, in particular certain periodic changes such as the circadian rhythm and seasonality, thus affecting the evolution of cooperation in spatial public goods games. By this means, periodic invasion is taken into account, which allows defectors with lower degrees than the initial value to randomly restore links and invade the population again. Through simulation, we find that the segregation strategy involving periodic invasion can effectively facilitate cooperation by formatting assortative and heterogeneous topology. Furthermore, we observe a subtle interplay between the costly topology control strategy and the exogenous changes in temporal factors that alter the spatiotemporal dynamics of coevolution and promote cooperation. We conclude that a relatively low periodic invasion frequency contributes to increasing the level of cooperation, but the threshold of cooperation is not sensitive to the change in invasion period when at longer intervals. We present our interpretations of these phenomena, which thus allow us to better understand the role of this new machine in the emergence of cooperation.

Kin selection for cooperation in natural bacterial populations

Bacteria produce a range of molecules that are secreted from the cell and can provide a benefit to the local population of cells. Laboratory experiments have suggested that these "public goods" molecules represent a form of cooperation, favored because they benefit closely related cells (kin selection). However, there is a relative lack of data demonstrating kin selection for cooperation in natural populations of bacteria. We used molecular population genetics to test for signatures of kin selection at the genomic level in natural populations of the opportunistic pathogen Pseudomonas aeruginosa We found consistent evidence from multiple traits that genes controlling putatively cooperative traits have higher polymorphism and greater divergence and are more likely to harbor deleterious mutations relative to genes controlling putatively private traits, which are expressed at similar rates. These patterns suggest that cooperative traits are controlled by kin selection, and we estimate that the relatedness for social interactions in P. aeruginosa is r = 0.84. More generally, our results demonstrate how molecular population genetics can be used to study the evolution of cooperation in natural populations.

Acculturation and the evolution of cooperation in spatial public goods games

Cooperation is one of the foundations of human society. Many solutions to cooperation problems have been developed and culturally transmitted across generations. Because immigration can play a role in nourishing or disrupting cooperation in societies, we must understand how the newcomers' culture interacts with the hosting culture. Here, we investigate the effect of different acculturation settings on the evolution of cooperation in spatial public goods games with the immigration of defectors and efficient cooperators. Here, immigrants may be socially influenced, or not, by the native culture according to four acculturation settings: integration, where immigrants imitate both immigrants and natives; marginalization, where immigrants do not imitate either natives or other immigrants; assimilation, where immigrants only imitate natives; and separation, where immigrants only imitate other immigrants. We found that cooperation is greatly facilitated and reaches a peak for moderate values of the migration rate under any acculturation setting. Most interestingly, we found that the main acculturation factor driving the highest levels of cooperation is that immigrants do not avoid social influence from their fellow immigrants. We also show that integration may not promote the highest level of native cooperation if the benefit of cooperation is low.

Wealth-based rule favors cooperation in costly public goods games when individual selection is inevitable

Individual selection, as an effective mechanism, is often used in spatial evolutionary games to promote cooperation. Previous research assumes that, individual selection usually occurs with people who fail to meet a certain criterion. However, individual selection is usually inevitable, regardless of whether players in population cooperate or defect. This paper studies the effects of wealth-based rule in costly public goods games when individual selection is inevitable. Specifically, we assume that only the top V individuals with relatively high cumulative payoffs in each group can be selected for costly PGG. The results show that when V is large, the increase of participation cost has slight inhibitory effects on the evolution of cooperation, but it alleviates the polarization of individuals. However, when V is small, the increase of participation cost within a certain range promotes cooperation prosperity, but it also causes an increase in the proportion of polarized individuals and a widening of the wealth gap between rich and poor individuals.

The role of alliance cooperation in spatial public goods game

Assistance and aiding partners exploited by defectors could be essential to avoid being exploited and expanding the payoff. The research on of human behaviors has suggested that organizations and alliances play an important role in promoting cooperation between humans. Therefore, this article studies the evolution of cooperation in spatial public goods games with alliance strategy on square lattice network where, in addition to the classical strategies of cooperation (C) and defection (D), alliance cooperators (A) are considered as an additional strategy. Alliance players will provide a portion of their payoff to aid their allies in the same group, who have been exploited by defectors. Apparently, alliance players demonstrate a remarkable ability sweep out defectors through network reciprocity. However, by analyzing the parameters, as influenced by cooperators, the cooperation level is a non-monotonic function of aid intensity and synergy factor. The results presented in this article can help to understand the role of alliance strategies, organizations, and taxes in promoting and maintaining cooperation in human society.

Punishment mechanisms and cooperation in public goods games: Experimental evidence

ABSTRACTThis paper proposes the majority‐voting punishment mechanism and compares its effect on the contribution decision with other punishment mechanisms when individuals have homogeneous or heterogeneous marginal per capita returns on public goods. The experimental results show that if individuals are homogeneous, the majority‐voting punishment mechanism is an alternative to encourage cooperation and reduce antisocial punishment. But, if individuals are heterogeneous, the individual and majority‐voting punishment mechanisms are similarly effective in promoting cooperation in the organization. Furthermore, whatever punishment mechanism is implemented, organizations should pay attention to the problem of antisocial punishment.

The evolution of cooperation in public goods games on signed networks

Evolutionary game theory describes a system in which individuals interact with each other. In recent years, the combination of complex network and evolutionary game theory, which is supposedly the best way to interpret how cooperate strategies are maintained in rational population pursuing maximum benefit, has gained considerable attention. There are numerous studies on public goods game (PGG), which is the classic laboratory paradigm for studying collective action problem. Now, we consider a PGG on the random signed network. Individuals interact and play games along the social ties defined by a signed network, where the positive links indicate the friendship and the negative links indicate the hostile relationship among the players. Here, we design an evolutionary mechanism: the rule is that a friendly relationship leads to a higher probability for a subject to imitate the neighbor with the highest payoff, whereas a hostile relationship leads to a less probability. Then, we conduct the game on four types of community structure signed networks, a random signed network, and two real-world signed networks. The simulation result indicates that there is a slight difference in the level of cooperation among the four clustering networks. In addition, the most interesting thing is that the negative edges hinder cooperation when the enhancement factor is low and promote the cooperation when the enhancement factor is high on the random signed network.