The collective-risk social dilemma and the prevention of simulated dangerous climate change

Evolution of cooperation under threshold public goods game

When the number of cooperators does not reach the collective target, resulting in the collective risk social dilemma, the self-organizing behavior of the group leads to the loss of collective interest and the government intervention leads to the increase of collective interest. For these two situations, we study the evolution of cooperation under threshold public goods game in well-mixed population. The results show that the introduction of the threshold makes it possible to generate complex dynamics with two interior equilibria in the replication equation. For self-organizing behavior, increasing the threshold is a double-edged sword. Although raising the threshold may increase the level of cooperation, the risk of dominance of defection also increases. For government intervention behavior, increasing the threshold significantly promotes cooperation. The common result is that individuals tend to free-ride when the group size increases. In addition, the greater the impact of the two behaviors on collective interest, the more conducive to promoting cooperation. When there are fewer initial cooperators, the government should intervene in time to generate cooperation. When there are more initial cooperators, self-organizing behavior is more conducive to attracting cooperators than government intervention. We hope that the model and results proposed in this paper can contribute to addressing the challenges posed by global issues such as climate change and the degradation of the ecological environment.

Gamify to persuade: A systematic review of gamified sustainable mobility

The increasing need to address climate change has intensified efforts to promote green transportation options, such as cycling and public transit. Over the past few decades, gamification-the integration of game-like elements into non-game contexts to motivate and engage people in adopting new behaviors-has emerged as a strategy to encourage the use of sustainable transportation. This literature review examines how gamification has been used to drive the adoption of green transportation. Following the PRISMA methodology, 49 documents were initially screened, leading to a final selection of 14 papers. We analyze the stakeholders involved, the game elements, the external rewards (e.g., financial incentives), and persuasive strategies employed, and the overall effectiveness of these initiatives both in the short and in the long term. We also explore the relationship between game elements and persuasive approaches, offering insights into how they are related. Finally, we propose a research agenda that emphasizes the exploration of different game elements and the need for a multidisciplinary approach to designing gameful systems that promote sustainable behaviors.

A new electoral bottom-up model of institutional governance

The sustainable governance of Global Risky Commons (GRC)-global commons in the presence of a sizable risk of overall failure-is ubiquitous and requires a global solution. A prominent example is the mitigation of the adverse effects of global warming. In this context, the Collective Risk Dilemma (CRD) provides a convenient baseline model which captures many important features associated with GRC type problems by formulating them as problems of cooperation. Here we make use of the CRD to develop, for the first time, a bottom-up institutional governance framework of GRC. We find that the endogenous creation of local institutions that require a minimum consensus amongst group members-who, in turn, decide the nature of the institution (reward/punishment) via an electoral process-leads to higher overall cooperation than previously proposed designs, especially at low risk, proving that carrots and sticks implemented through local voting processes are more powerful than other designs. The stochastic evolutionary game theoretical model framework developed here further allows us to directly compare our results with those stemming from previous models of institutional governance. The model and the methods employed here are relevant and general enough to be applied to a variety of contemporary interdisciplinary problems.

Co-evolution of behaviour and beliefs in social dilemmas: estimating material, social, cognitive and cultural determinants

Understanding and predicting human cooperative behaviour and belief dynamics remains a major challenge both from the scientific and practical perspectives. Because of the complexity and multiplicity of material, social and cognitive factors involved, both empirical and theoretical work tends to focus only on some snippets of the puzzle. Recently, a mathematical theory has been proposed that integrates material, social and cognitive aspects of behaviour and beliefs dynamics to explain how people make decisions in social dilemmas within heterogeneous groups. Here we apply this theory in two countries, China and Spain, through four long-term behavioural experiments utilising the Common Pool Resources game and the Collective Risk game. Our results show that material considerations carry the smallest weight in decision-making, while personal norms tend to be the most important factor. Empirical and normative expectations have intermediate weight in decision-making. Cognitive dissonance, social projection, logic constraints and cultural background play important roles in both decision-making and beliefs dynamics. At the individual level, we observe differences in the weights that people assign to factors involved in the decision-making and belief updating process. We identify different types of prosociality and rule-following associated with cultural differences, various channels for the effects of messaging, and culturally dependent interactions between sensitivity to messaging and conformity. Our results can put policy and information design on firmer ground, highlighting the need for interventions tailored to the situation at hand and to individual characteristics. Overall, this work demonstrates the theoretical and practical power of the theory in providing a more comprehensive understanding of human behaviour and beliefs.

Co-evolution of risk and cooperation in climate policies under wealth inequality

Worldwide cooperation is necessary to mitigate the effects of climate change. Many previous investigations employed the so-called collective risk dilemma, where the risk of losing everything whenever a target is not met was fixed from the outset, rendering predictions dependent on snapshot values assumed for this parameter, whose importance was found to be paramount. Here, we couple risk with the overall success of mitigation, investigating the co-evolution of risk and cooperation in a world where countries are partitioned in two different wealth classes, allowing us to further assess the impact of wealth inequality and homophily on the co-evolutionary dynamics. We show that the stochastic dynamics is dominated by a global attractor, typically located in a region of low risk, where most developed countries cooperate most of the time while developing countries cooperate to a lesser extent. This scenario assumes no homophily which, when moderate, can contribute to increase overall cooperation, more so when combined with the presence of a small fraction of developing countries that opt for an unconditional cooperative behavior.

Cooperation in the face of crisis: effect of demographic noise in collective-risk social dilemmas

In deciding whether to contribute to a public good, people often face a social dilemma known as the tragedy of the commons: either bear the cost of promoting the collective welfare, or free-ride on the efforts of others. Here, we study the dynamics of cooperation in the context of the threshold public goods games, in which groups must reach a cumulative target contribution to prevent a potential disaster, such as an environmental crisis or social unrest, that could result in the loss of all private wealth. The catch is that the crisis may never materialize, and the investment in the public good is lost. Overall, higher risk of loss promotes cooperation, while larger group size tends to undermine it. For most parameter settings, free-riders (defectors) cannot be eliminated from the population, leading to a coexistence equilibrium between cooperators and defectors for infinite populations. However, this equilibrium is unstable under the effect of demographic noise (finite population), since the cooperator-only and defector-only states are the only absorbing states of the stochastic dynamics. We use simulations and finite-size scaling to show that cooperators eventually die off and derive scaling laws for the transient lifetimes or half-lives of the coexistence metastable state. We find that for high risk, the half-life of cooperators increases exponentially with population size, while for low risk, it decreases exponentially with population size. At the risk threshold, where the coexistence regime appears in a discontinuous manner, the half-life increases with a power of the population size.

A complete classification of evolutionary games with environmental feedback

A tragedy of the commons, in which rational behavior of individuals to maximize their own payoffs depletes common resources, is one of the most important research topics in game theory. To better understand the social dilemma problem, recent studies have developed a theoretical framework of feedback-evolving game where individual behavior affects an environmental (renewable) resource and the environmental resource changes individual payoffs. While previous studies assumed that the frequency of defectors increases (prisoner's dilemma [PD] game) when the environmental resource is abundant to investigate an oscillating tragedy of the commons, it is also possible for other types of game to produce the social dilemma. In this paper, we extend the feedback-evolving game by considering not only PD game, but also the other three game structures when the environmental resource is replete for a reasonably complete classification. The three games are Chicken game where defectors and cooperators coexist through minority advantage, Stag-Hunt (SH) game with minority disadvantage, and Trivial game where the frequency of cooperators increases. In addition, we utilize a dilemma phase plane to visually track (transient) dynamics of game structure changes. We found that an emergent initial condition dependence (i.e. bistability) is pervasive in the feedback-evolving game when the three games are involved. We also showed that persistent oscillation dynamics arise even with Chicken or SH games in replete environments. Our generalized analysis will be an important step to further extend the theoretical framework of feedback-evolving game to various game situations with environmental feedback.

Children Sustain Cooperation in a Threshold Public-Goods Game Even When Seeing Others' Outcomes

Many societal challenges are threshold dilemmas requiring people to cooperate to reach a threshold before group benefits can be reaped. Yet receiving feedback about others' outcomes relative to one's own (relative feedback) can undermine cooperation by focusing group members' attention on outperforming each other. We investigated the impact of relative feedback compared to individual feedback (only seeing one's own outcome) on cooperation in children from Germany and India (6- to 10-year-olds, N = 240). Using a threshold public-goods game with real water as a resource, we show that, although feedback had an effect, most groups sustained cooperation at high levels in both feedback conditions until the end of the game. Analyses of children's communication (14,374 codable utterances) revealed more references to social comparisons and more verbal efforts to coordinate in the relative-feedback condition. Thresholds can mitigate the most adverse effects of social comparisons by focusing attention on a common goal.

Threshold incentive mechanisms for the sustainable management of public resources

Maintaining global ecological balance is inextricably linked to the effective governance of public resources. Previous studies have proposed the introduction of incentive mechanisms to mitigate the defection behavior within the scope of public resource management to facilitate sustainable utilization. However, these incentive strategies often present a considerable financial burden. Here, we first propose a two-threshold incentive scheme based on group state objectives, where the reward mechanism is triggered when the number of cooperators is below the threshold M, and the punishment mechanism is triggered when the number of cooperators is above the threshold Q. We further introduce an incentive mechanism by considering both resource and group thresholds, where incentives are implemented separately when the number of cooperators and the current quantity of resources meet thresholds. Our theoretical results reveal that introducing these two new mechanisms can effectively maintain cooperative behavior and sustainable resources while reducing management costs. However, if the initial resource level is low, the tragedy of the commons will still occur. It is recommended that the number of developers be reduced, the allocation be lowered, or the development simply suspended and the natural regeneration of resources be waited for.

Frequency-dependent returns in nonlinear public goods games

When individuals interact in groups, the evolution of cooperation is traditionally modelled using the framework of public goods games. These models often assume that the return of the public goods depends linearly on the fraction of contributors. In contrast, in real-life public goods interactions, the return can depend on the size of the investor pool as well. Here, we consider a model in which the multiplication factor (marginal per capita return) for the public goods depends linearly on how many contribute, which results in a nonlinear model of public goods. This simple model breaks the curse of dominant defection found in linear public goods interactions and gives rise to richer dynamical outcomes in evolutionary settings. We provide an in-depth analysis of the more varied decisions by the classical rational player in nonlinear public goods interactions as well as a mechanistic, microscopic derivation of the evolutionary outcomes for the stochastic dynamics in finite populations and in the deterministic limit of infinite populations. This kind of nonlinearity provides a natural way to model public goods with diminishing returns as well as economies of scale.

Collective action within an environment of unknown unknowns: Experiences with the port of Mars Game

There is limited research about how groups solve collective action problems in uncertain environments, especially if groups are confronted with unknown unknowns. We aim to develop a more comprehensive view of the characteristics that allow both groups and individuals to navigate such issues more effectively. In this article, we present the results of a new online experiment where individuals make decisions of whether to contribute to the group or pursue self-interest in an environment with high uncertainty, including unknown unknowns. The behavioral game, Port of Mars is framed as a first-generation habitat on Mars where participants have to make decisions on how much to invest in the shared infrastructure to maintain system health and how much to invest in personal goals. Participants can chat during the game, and take surveys before and after the game in order to measure personality attributes and observations from the game. Initial results suggest that a higher average social value orientation and more communication are the key factors that explain why some groups are more successful than others in surviving Port of Mars. Neither other attributes of players nor the group's communication content explain the observed differences between groups.

An outside individual option increases optimism and facilitates collaboration when groups form flexibly

Voluntary participation is a central yet understudied aspect of collaboration. Here, we model collaboration as people's voluntary choices between joining an uncertain public goods provisioning in groups and pursuing a less profitable but certain individual option. First, we find that voluntariness in collaboration increases the likelihood of group success via two pathways, both contributing to form more optimistic groups: pessimistic defectors are filtered out from groups, and some individuals update their beliefs to become cooperative. Second, we reconcile these findings with existing literature that highlights the detrimental effects of an individual option. We argue that the impact of an outside individual option on collaboration depends on the "externality" of loners - the influence that those leaving the group still exert on group endeavors. Theoretically and experimentally, we show that if collaboration allows for flexible group formation, the negative externality of loners remains limited, and the presence of an individual option robustly aids collaborative success.

Committing to the wrong artificial delegate in a collective-risk dilemma is better than directly committing mistakes

While autonomous artificial agents are assumed to perfectly execute the strategies they are programmed with, humans who design them may make mistakes. These mistakes may lead to a misalignment between the humans' intended goals and their agents' observed behavior, a problem of value alignment. Such an alignment problem may have particularly strong consequences when these autonomous systems are used in social contexts that involve some form of collective risk. By means of an evolutionary game theoretical model, we investigate whether errors in the configuration of artificial agents change the outcome of a collective-risk dilemma, in comparison to a scenario with no delegation. Delegation is here distinguished from no-delegation simply by the moment at which a mistake occurs: either when programming/choosing the agent (in case of delegation) or when executing the actions at each round of the game (in case of no-delegation). We find that, while errors decrease success rate, it is better to delegate and commit to a somewhat flawed strategy, perfectly executed by an autonomous agent, than to commit execution errors directly. Our model also shows that in the long-term, delegation strategies should be favored over no-delegation, if given the choice.

Intergenerational altruism and climate policy preferences

Climate mitigation constitutes an intergenerational moral dilemma; the decisions we make today will inevitably shape the prospects for generations to come. Yet, we still know little about the relationship between intergenerational altruism (IGA)-our concerns for the well-being of future generations-and support for costly climate mitigation policies. In this study, we present an approach to measuring IGA through an intergenerational dilemma, where participants allocate resources across generations. First, we describe how IGA depends on the temporal (social) distance between generations and demonstrate robust correlations between IGA and support for several climate policies. Then, we leverage randomized participation in the intergenerational dilemma to show that it causally increases climate policy support, an effect we attribute to higher worries about human-induced climate change among treated subjects. An exploratory heterogeneity analysis suggests that the impact of the intergenerational dilemma is primarily driven by female and nonbinary participants. In sum, this study presents both a novel measurement strategy and robust evidence of a malleable moral basis of climate policy preferences.

Efficiency or equality? The utilitarianism-egalitarianism trade-off determines carbon allocation preference

International carbon allocation confronts the conflict between efficiency and equality. Previous research based on the intergroup bias perspective has attributed carbon allocation preference to the defence of ingroup interests (i.e., national interests) while overlooking the critical role of trade-offs between competing moral values. Integrating the contingency theory of justice and moral philosophical theories of utilitarianism and egalitarianism, we proposed that the moral-values trade-off between utilitarianism and egalitarianism determines carbon allocation preference through justice reasoning. Analysis of large-scale survey datasets (Study 1) revealed that aggregated national endorsement of utilitarianism over egalitarianism predicted greater efficiency preference in total and per capita carbon emission levels. Study 2 demonstrated that experimentally manipulating endorsement of utilitarianism versus egalitarianism boosted efficiency (vs. equality) preference in carbon allocation, and justice reasoning characterized by enhanced efficiency-focused justice and diminished equality-focused justice accounted for these effects. Using a 'manipulation-of-mediator' design, Study 3 further confirmed the causal link in the mediation model. By highlighting the significance of moral trade-offs in shaping carbon allocation preference, this research not only provides a novel moral perspective in understanding debates on international carbon allocation but also has important implications for fostering international carbon abatement cooperation.

Political reinforcement learners

Politics can seem home to the most calculating and yet least rational elements of humanity. How might we systematically characterize this spectrum of political cognition? Here, we propose reinforcement learning (RL) as a unified framework to dissect the political mind. RL describes how agents algorithmically navigate complex and uncertain domains like politics. Through this computational lens, we outline three routes to political differences, stemming from variability in agents' conceptions of a problem, the cognitive operations applied to solve the problem, or the backdrop of information available from the environment. A computational vantage on maladies of the political mind offers enhanced precision in assessing their causes, consequences, and cures.

Assessing the effects of pandemic risk on cooperation and social norms using a before-after Covid-19 comparison in two long-term experiments

How does threat from disease shape our cooperative actions and the social norms that guide such behaviour? To study these questions, we draw on a collective-risk social dilemma experiment that we ran before the emergence of the Covid-19 pandemic (Wave 1, 2018) and compare this to its exact replication, sampling from the same population, that we conducted during the first wave of the pandemic (Wave 2, 2020). Tightness-looseness theory predicts and evidence generally supports that both cooperation and accompanying social norms should increase, yet, we mostly did not find this. Contributions, the probability of reaching the threshold (cooperation), and the contents of the social norm (how much people should contribute) remained similar across the waves, although the strength of these social norms were slightly greater in Wave 2. We also study whether the results from Wave 1 that should not be affected by the pandemic-the relationship between social norms and cooperation and specific behavioural types-replicate in Wave 2 and find that these results generally hold. Overall, our work demonstrates that social norms are important drivers of cooperation, yet, communicable diseases, at least in the short term, have little or no effects on either.

Santos F, Simoens P, Lenaerts T. The art of compensation: How hybrid teams solve collective-risk dilemmas

It is widely known how the human ability to cooperate has influenced the thriving of our species. However, as we move towards a hybrid human-machine future, it is still unclear how the introduction of artificial agents in our social interactions affect this cooperative capacity. In a one-shot collective risk dilemma, where enough members of a group must cooperate in order to avoid a collective disaster, we study the evolutionary dynamics of cooperation in a hybrid population. In our model, we consider a hybrid population composed of both adaptive and fixed behavior agents. The latter serve as proxies for the machine-like behavior of artificially intelligent agents who implement stochastic strategies previously learned offline. We observe that the adaptive individuals adjust their behavior in function of the presence of artificial agents in their groups to compensate their cooperative (or lack of thereof) efforts. We also find that risk plays a determinant role when assessing whether or not we should form hybrid teams to tackle a collective risk dilemma. When the risk of collective disaster is high, cooperation in the adaptive population falls dramatically in the presence of cooperative artificial agents. A story of compensation, rather than cooperation, where adaptive agents have to secure group success when the artificial agents are not cooperative enough, but will rather not cooperate if the others do so. On the contrary, when risk of collective disaster is low, success is highly improved while cooperation levels within the adaptive population remain the same. Artificial agents can improve the collective success of hybrid teams. However, their application requires a true risk assessment of the situation in order to actually benefit the adaptive population (i.e. the humans) in the long-term.

Emotion expression and cooperation under collective risks

The difficulties associated with solving Humanity's major global challenges have increasingly led world leaders and everyday citizens to publicly adopt strong emotional responses, with either mixed or unknown impacts on others' actions. Here, we present two experiments showing that non-verbal emotional expressions in group interactions play a critical role in determining how individuals behave when contributing to public goods entailing future and uncertain returns. Participants' investments were not only shaped by emotional expressions but also enhanced by anger when compared with joy. Our results suggest that global coordination may benefit from interaction in which emotion expressions can be paramount.

When fairness is not enough: The disproportionate contributions of the poor in a collective action problem

Many of our most pressing challenges, from combating climate change to dealing with pandemics, are collective action problems: situations in which individual and collective interests conflict with each other. In such situations, people face a dilemma about making individually costly but collectively beneficial contributions to the common good. Understanding which factors influence people's willingness to make these contributions is vital for the design of policies and institutions that support the attainment of collective goals. In this study, we investigate how inequalities, and different causes of inequalities, impact individual-level behavior and group-level outcomes. First, we find that what people judged to be fair was not enough to solve the collective action problem: if they acted according to what they thought was fair, they would collectively fail. Second, the level of wealth (rich vs. poor) altered what was judged to be a fair contribution to the public good more than the cause of wealth (merit vs. luck vs. uncertain). Contributions during the game reflected these fairness judgments, with poorer individuals consistently contributing a higher proportion of their wealth than richer participants, which further increased inequality-particularly in successful groups. Finally, the cause of one's wealth was largely irrelevant, mattering most only when it was uncertain, as opposed to resulting from merit or luck. We discuss implications for policymakers and international climate change negotiations. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Evolution of conditional cooperation in collective-risk social dilemma with repeated group interactions

The evolution and long-term sustenance of cooperation has consistently piqued scholarly interest across the disciplines of evolutionary biology and social sciences. Previous theoretical and experimental studies on collective risk social dilemma games have revealed that the risk of collective failure will affect the evolution of cooperation. In the real world, individuals usually adjust their decisions based on environmental factors such as risk intensity and cooperation level. However, it is still not well understood how such conditional behaviours affect the evolution of cooperation in repeated group interactions scenario from a theoretical perspective. Here, we construct an evolutionary game model with repeated interactions, in which defectors decide whether to cooperate in subsequent rounds of the game based on whether the risk exceeds their tolerance threshold and whether the number of cooperators exceeds the collective goal in the early rounds of the game. We find that the introduction of conditional cooperation strategy can effectively promote the emergence of cooperation, especially when the risk is low. In addition, the risk threshold significantly affects the evolutionary outcomes, with a high risk promoting the emergence of cooperation. Importantly, when the risk of failure to reach collective goals exceeds a certain threshold, the timely transition from a defective strategy to a cooperative strategy by conditional cooperators is beneficial for maintaining high-level cooperation.

Human-environment feedback and the consistency of proenvironmental behavior

Addressing global environmental crises such as anthropogenic climate change requires the consistent adoption of proenvironmental behavior by a large part of a population. Here, we develop a mathematical model of a simple behavior-environment feedback loop to ask how the individual assessment of the environmental state combines with social interactions to influence the consistent adoption of proenvironmental behavior, and how this feeds back to the perceived environmental state. In this stochastic individual-based model, individuals can switch between two behaviors, 'active' (or actively proenvironmental) and 'baseline', differing in their perceived cost (higher for the active behavior) and environmental impact (lower for the active behavior). We show that the deterministic dynamics and the stochastic fluctuations of the system can be approximated by ordinary differential equations and a Ornstein-Uhlenbeck type process. By definition, the proenvironmental behavior is adopted consistently when, at population stationary state, its frequency is high and random fluctuations in frequency are small. We find that the combination of social and environmental feedbacks can promote the spread of costly proenvironmental behavior when neither, operating in isolation, would. To be adopted consistently, strong social pressure for proenvironmental action is necessary but not sufficient-social interactions must occur on a faster timescale compared to individual assessment, and the difference in environmental impact must be small. This simple model suggests a scenario to achieve large reductions in environmental impact, which involves incrementally more active and potentially more costly behavior being consistently adopted under increasing social pressure for proenvironmentalism.

Sustainability, Collective Self-Regulation, and Human-Nature Interdependence

Like any organism, humanity constructs its niche and adapts to the rest of nature by modifying available materials around them. In the era that some have dubbed the "Anthropocene," human niche construction has gone so far as to threaten the planetary climate system. The central question of sustainability is how humanity can collectively self-regulate niche construction, that is, humanity's relationship with the rest of nature. In this article, we argue that to resolve the collective self-regulation problem for sustainability, sufficiently accurate and relevant aspects of causal knowledge about the functioning of complex social-ecological systems need to be cognized, communicated, and collectively shared. More specifically, causal knowledge about human-nature interdependence-how humans interact with each other and the rest of nature-is critical for coordinating cognitive agents' thoughts, feelings, and actions for the greater good without falling into the trap of free riding. Here, we will develop a theoretical framework to consider the role of causal knowledge about human-nature interdependence in collective self-regulation for sustainability, review the relevant empirical research primarily focusing on climate change, and take stock of what is currently known and what we need to investigate in the future.

Government regulation strategy, leading firms' innovation strategy, and following firms imitation strategy: An analysis based on evolutionary game theory

In the innovation ecosystem, the knowledge-based game behavior of each subject not only pertains to its own survival and development but also affects evolution of the innovation ecosystem. The present study investigates the choice of government's regulation strategy, leading firms' innovation protection strategy and following firms' imitation strategy from the perspective of group evolutionary game. Based on the cost-benefit perspective, an asymmetric tripartite evolutionary game model and a simulation model are constructed to analyze the strategies and stability of the evolutionary equilibrium of each subject. We focus mainly on the protection intensity of innovation achievements by leading enterprises and the difficulty of imitation and substitution by following enterprises. The cost of patent operation and maintenance, government subsidies, and the relative difficulty of technology substitution and imitation were identified as the key factors affecting the evolutionary equilibrium of the system. Based on different scenarios resulting from the aforementioned factors, four equilibrium states are observed in the system, namely {no government regulation, technology secrecy, substitution}, {no government regulation, technology secrecy, imitation}, {no government regulation, patent application, imitation}, and {government regulation, patent application, imitation}. Finally, the study suggests corresponding recommendations for the three parties, which can help governments as well as the leading and following firms to choose appropriate behavioral strategies. At the same time, this study offers positive insights to participants in the global innovation ecosystem.

Coevolutionary dynamics via adaptive feedback in collective-risk social dilemma game

Human society and natural environment form a complex giant ecosystem, where human activities not only lead to the change in environmental states, but also react to them. By using collective-risk social dilemma game, some studies have already revealed that individual contributions and the risk of future losses are inextricably linked. These works, however, often use an idealistic assumption that the risk is constant and not affected by individual behaviors. Here, we develop a coevolutionary game approach that captures the coupled dynamics of cooperation and risk. In particular, the level of contributions in a population affects the state of risk, while the risk in turn influences individuals' behavioral decision-making. Importantly, we explore two representative feedback forms describing the possible effect of strategy on risk, namely, linear and exponential feedbacks. We find that cooperation can be maintained in the population by keeping at a certain fraction or forming an evolutionary oscillation with risk, independently of the feedback type. However, such evolutionary outcome depends on the initial state. Taken together, a two-way coupling between collective actions and risk is essential to avoid the tragedy of the commons. More importantly, a critical starting portion of cooperators and risk level is what we really need for guiding the evolution toward a desired direction.

Cooperation and coordination in heterogeneous populations

One landmark application of evolutionary game theory is the study of social dilemmas. This literature explores why people cooperate even when there are strong incentives to defect. Much of this literature, however, assumes that interactions are symmetric. Individuals are assumed to have the same strategic options and the same potential pay-offs. Yet many interesting questions arise once individuals are allowed to differ. Here, we study asymmetry in simple coordination games. In our set-up, human participants need to decide how much of their endowment to contribute to a public good. If a group's collective contribution reaches a pre-defined threshold, all group members receive a reward. To account for possible asymmetries, individuals either differ in their endowments or their productivities. According to a theoretical equilibrium analysis, such games tend to have many possible solutions. In equilibrium, group members may contribute the same amount, different amounts or nothing at all. According to our behavioural experiment, however, humans favour the equilibrium in which everyone contributes the same proportion of their endowment. We use these experimental results to highlight the non-trivial effects of inequality on cooperation, and we discuss to which extent models of evolutionary game theory can account for these effects. This article is part of the theme issue 'Half a century of evolutionary games: a synthesis of theory, application and future directions'.

The future of theoretical evolutionary game theory

Evolutionary game theory is a truly interdisciplinary subject that goes well beyond the limits of biology. Mathematical minds get hooked up in simple models for evolution and often gradually move into other parts of evolutionary biology or ecology. Social scientists realize how much they can learn from evolutionary thinking and gradually transfer insight that was originally generated in biology. Computer scientists can use their algorithms to explore a new field where machines not only learn from the environment, but also from each other. The breadth of the field and the focus on a few very popular issues, such as cooperation, comes at a price: several insights are re-discovered in different fields under different labels with different heroes and modelling traditions. For example, reciprocity or spatial structure are treated differently. Will we continue to develop things in parallel? Or can we converge to a single set of ideas, a single tradition and eventually a single software repository? Or will these fields continue to cross-fertilize each other, learning from each other and engaging in a constructive exchange between fields? Ultimately, the popularity of evolutionary game theory rests not only on its explanatory power, but also on the intuitive character of its models. This article is part of the theme issue 'Half a century of evolutionary games: a synthesis of theory, application and future directions'.

Interdependent Self-Organizing Mechanisms for Cooperative Survival

Cooperative survival "games" are situations in which, during a sequence of catastrophic events, no one survives unless everyone survives. Such situations can be further exacerbated by uncertainty over the timing and scale of the recurring catastrophes, while the resource management required for survival may depend on several interdependent subgames of resource extraction, distribution, and investment with conflicting priorities and preferences between survivors. In social systems, self-organization has been a critical feature of sustainability and survival; therefore, in this article we use the lens of artificial societies to investigate the effectiveness of socially constructed self-organization for cooperative survival games. We imagine a cooperative survival scenario with four parameters: scale, that is, n in an n-player game; uncertainty, with regard to the occurrence and magnitude of each catastrophe; complexity, concerning the number of subgames to be simultaneously "solved"; and opportunity, with respect to the number of self-organizing mechanisms available to the players. We design and implement a multiagent system for a situation composed of three entangled subgames-a stag hunt game, a common-pool resource management problem, and a collective risk dilemma-and specify algorithms for three self-organizing mechanisms for governance, trading, and forecasting. A series of experiments shows, as perhaps expected, a threshold for a critical mass of survivors and also that increasing dimensions of uncertainty and complexity require increasing opportunity for self-organization. Perhaps less expected are the ways in which self-organizing mechanisms may interact in pernicious but also self-reinforcing ways, highlighting the need for some reflection as a process in collective self-governance for cooperative survival.

Deterrence through punishment can resolve collective risk dilemmas in carbon emission games

Collective risk social dilemmas are at the heart of the most pressing global challenges we are facing today, including climate change mitigation and the overuse of natural resources. Previous research has framed this problem as a public goods game (PGG), where a dilemma arises between short-term interests and long-term sustainability. In the PGG, subjects are placed in groups and asked to choose between cooperation and defection, while keeping in mind their personal interests as well as the commons. Here, we explore how and to what extent the costly punishment of defectors is successful in enforcing cooperation by means of human experiments. We show that an apparent irrational underestimation of the risk of being punished plays an important role, and that for sufficiently high punishment fines, this vanishes and the threat of deterrence suffices to preserve the commons. Interestingly, however, we find that high fines not only avert freeriders, but they also demotivate some of the most generous altruists. As a consequence, the tragedy of the commons is predominantly averted due to cooperators that contribute only their "fair share" to the common pool. We also find that larger groups require larger fines for the deterrence of punishment to have the desired prosocial effect.

Information about historical emissions drives the division of climate change mitigation costs

Despite worsening climate change, the international community still disagrees on how to divide the costs of mitigation between developing countries and developed countries, which emitted the bulk of historical carbon emissions. We study this issue using an economic experiment. Specifically, we test how information about historical emissions influences how much participants pay for climate change mitigation. In a four-player game, participants are assigned to lead two fictional countries as members of either the first or the second generation. The first generation produces wealth at the expense of greater carbon emissions. The second generation inherits their predecessor's wealth and negotiates how to split the climate change mitigation costs. Here we show that when the second generation knows that the previous generation created the current wealth and mitigation costs, participants whose predecessor generated more carbon emissions offered to pay more, whereas the successors of low-carbon emitters offered to pay less.

Intergenerational and intragenerational preferences in a developing country to avoid climate change

Intergenerational and intragenerational approaches to climate change take into account the actions taken by the current generation to maintain or improve the climate, which is advantageous to both the present and future generations. Climate-friendly initiatives primarily benefit future generations, with current generations receiving lesser benefits. Self-interest can hinder the management of shared resources, as seen in the "tragedy of the commons" concept, where individuals benefit from defecting, but society bears the consequences of it. This study used three different time horizons to determine the inter- and intra-generational preferences of groups of human subjects for preventing hazardous climate change. We looked at how groups of participants responded in scenarios that varied in motivation, income, social pressure, and learning opportunities. For this purpose, we conducted two group experiments framed around climate change where participants could choose to cooperate for a noble cause: tree plantations. Its rewards are delayed by several years and probably a few decades (intergenerational discounting), where future generations will be the big beneficiaries. There were two more options: the first one delayed the reward by 1 week, and the second was delayed by seven weeks (intragenerational discounting). We found that intergenerational discounting was high when the groups had free will and motivation. Further, it is revealed that having more money does not play a significant positive role in long-term climate sustainability in a developing country; however, it does, but not as much as motivation and free will do.

Generic catastrophic poverty when selfish investors exploit a degradable common resource

The productivity of a common pool of resources may degrade when overly exploited by a number of selfish investors, a situation known as the tragedy of the commons. Without regulations, agents optimize the size of their individual investments into the commons by balancing incurring costs with the returns received. The resulting Nash equilibrium involves a self-consistency loop between individual investment decisions and the state of the commons. As a consequence, several non-trivial properties emerge. For N investing actors we prove rigorously that typical payoffs do not scale as 1/N, the expected result for cooperating agents, but as (1/N)². Payoffs are hence reduced with regard to the functional dependence on N, a situation denoted catastrophic poverty. We show that catastrophic poverty results from a fine-tuned balance between returns and costs. Additionally, a finite number of oligarchs may be present. Oligarchs are characterized by payoffs that are finite and not decreasing when N increases. Our results hold for generic classes of models, including convex and moderately concave cost functions. For strongly concave cost functions the Nash equilibrium undergoes a collective reorganization, being characterized instead by entry barriers and sudden death forced market exits.

Behavioral paradigms for studying pro-environmental behavior: A systematic review

In view of global environmental deterioration and climate change, researchers from multiple fields of the behavioral sciences examine the determinants of pro-environmental behavior. Research on pro-environmental behavior is dominated by the use of self-report measures, which relates to critical validity problems. Some of these problems can be addressed by studying consequential behavior in behavioral paradigms (i.e., systematically arranged situations of actual environmental relevance). However, pro-environmental behavior paradigms have been scattered across disciplines, and many researchers may not be aware of the wealth of available paradigms. The present review aims to acquaint researchers across disciplinary borders with the behavioral paradigms developed to study pro-environmental behavior in different domains. A systematic literature search revealed 99 ad hoc paradigms and five validated paradigms of pro-environmental behavior. I review how different authors have succeeded in implementing the consequences of pro-environmental behavior in standardized field, laboratory, or online situations, point to caveats in the use of behavioral paradigms, and illustrate how researchers can select a paradigm for their own research.

Fairness of Ratemaking for Catastrophe Insurance: Lessons from Machine Learning

A hallmark of information technology use in disaster management is the wide adoption of complex information systems for risk assessment, portfolio management, and ratemaking in catastrophe insurance. Whereas the importance of catastrophe insurance to disaster preparedness is beyond dispute, catastrophe insurers are increasingly reckoning with the potential impact of inequality in insurance practices. Historically, the presence of inequalities in insurance, from redlining to pricing disparity, has had a devastating impact on minority communities. Even recently, people living in predominantly African American communities can still be charged more for the same insurance coverage than people living in other communities. Whereas the fairness of insurance ratemaking is studied in general, we identify a unique challenge for catastrophe insurance that sets it apart from other lines of insurance. Drawing upon the recent advances in machine learning for fair data valuation, we reveal striking connections between the two seemingly unrelated problems and lean on insights from machine learning to study the fairness of ratemaking methods for catastrophe insurance. Our results indicate the potential existence of disparate impact against minorities across existing methods, pointing to a unique solution that can satisfy a few commonly assumed properties of fair ratemaking for catastrophe insurance.

Anticipatory Threat Mitigates the Breakdown of Group Cooperation

Humans are exposed to environmental and economic threats that can profoundly affect individual survival and group functioning. Although anecdotal evidence suggests that threat exposure can increase collective action, the effects of threat on decision-making have been mainly investigated at the individual level. Here we examine how threat exposure and concomitant physiological responses modulate cooperation in small groups. Individuals (N = 105, ages 18-34 years) in groups of three were exposed to threat of electric shocks while deciding how much to contribute to a public good. Threat of shock induced a state of physiological freezing and, compared with no-threat conditions, reduced free riding and enabled groups to maintain higher cooperation over time. Exploratory analyses revealed that more cooperative responses under threat were driven by stronger baseline prosociality, suggesting that habitual prosociality is reinforced under threat. The current results support the view that human groups respond to outside threat with increased cooperation.

Economic experiments support Ostrom's polycentric approach to mitigating climate change

The late Nobel laureate Elinor Ostrom envisioned a polycentric approach to mitigating climate change rather than a centralised solution. Debating about global efforts to solve climate-change problems has yet not led to an effective global treaty. Ostrom argued that instead of focusing only on global efforts, it is better to encourage polycentric efforts to reduce the risks associated with the emission of greenhouse gases. Many problems conceptualised as 'global problems' are the cumulative results of actions taken by individuals, families, small groups, private firms, and local, regional, and national governments. Ostrom and colleagues pointed to many examples of successfully managing a common good through interaction within a community. Energy-saving actions undertaken by individuals, families and actors at a small-scale pay off and, when multiplied, may reduce emissions globally. The incentive to achieve an individual net gain may trigger human investment decisions. Here we provide experimental support for Ostrom's basic ideas using methods of experimental economics. By subdividing experimental populations in subgroups that approach sub-goals of mitigating simulated dangerous climate change combined with incentives, the 'global' solution is achieved by combined subgroup contributions exceeding the 'global' threshold for averting simulated dangerous climate change. Incentives from refunded saved energy motivate reaching sub-goals, as Ostrom suggested. By contrast, coercing free-riding subgroups through sanctioning at a cost fails, because sanctioning also hits fair individuals who then reduce their contributions. However, the power of polycentricity with numerous successful units can help mitigate climate change.

Social dilemma in the excess use of antimicrobials incurring antimicrobial resistance

The emergence of antimicrobial resistance (AMR) caused by the excess use of antimicrobials has come to be recognized as a global threat to public health. There is a 'tragedy of the commons' type social dilemma behind this excess use of antimicrobials, which should be recognized by all stakeholders. To address this global threat, we thus surveyed eight countries/areas to determine whether people recognize this dilemma and showed that although more than half of the population pays little, if any, attention to it, almost 20% recognize this social dilemma, and 15-30% of those have a positive attitude toward solving that dilemma. We suspect that increasing individual awareness of this social dilemma contributes to decreasing the frequency of AMR emergencies.

The Black Box as a Control for Payoff-Based Learning in Economic Games

The black box method was developed as an "asocial control" to allow for payoff-based learning while eliminating social responses in repeated public goods games. Players are told they must decide how many virtual coins they want to input into a virtual black box that will provide uncertain returns. However, in truth, they are playing with each other in a repeated social game. By "black boxing" the game's social aspects and payoff structure, the method creates a population of self-interested but ignorant or confused individuals that must learn the game's payoffs. This low-information environment, stripped of social concerns, provides an alternative, empirically derived null hypothesis for testing social behaviours, as opposed to the theoretical predictions of rational self-interested agents (Homo economicus). However, a potential problem is that participants can unwittingly affect the learning of other participants. Here, we test a solution to this problem in a range of public goods games by making participants interact, unknowingly, with simulated players ("computerised black box"). We find no significant differences in rates of learning between the original and the computerised black box, therefore either method can be used to investigate learning in games. These results, along with the fact that simulated agents can be programmed to behave in different ways, mean that the computerised black box has great potential for complementing studies of how individuals and groups learn under different environments in social dilemmas.

Societal Collapse and Intergenerational Disparities in Suffering

The collapse of society is inevitable, even if it is in the distant future. When it collapses, it is likely to do so within the lifetimes of some people. These people will have matured in pre-collapse society, experience collapse, and then live the remainder of their lives in the post-collapse world. I argue that this group of people—the transitional generation—will be the worst off from societal collapse, far worse than subsequent generations. As the transitional generation, they will suffer disparately. This intergenerational disparity in suffering is inequitable. Given that other disparities in suffering are worthy of remediation, this intergenerational disparity in suffering is worthy of remediation. However, the only way to do so is to target the mental states of the members of the transitional generation.

Modelling pandemic behaviour using an economic multiplayer game

During a pandemic, isolating oneself from the community limits viral transmission and helps avoid repeated societal lockdowns. This entails a social dilemma—either distance oneself from others for the benefit of the public good or free-ride and enjoy the benefits of freedom. It is not yet understood how the unfamiliar incentive structure and interpersonal context presented by a pandemic together modulate individuals’ approach to this social dilemma. In this preregistered study, we take a game-theoretical approach and investigate people’s decisions to self-isolate, using a novel iterated multiplayer game designed to capture the decision-making environment in the pandemic. To elucidate players’ thinking, we use a variation of the strategy method and elicit beliefs about how much others will self-isolate. Players tend to respond to social norms with abidance, rather than transgression; they resist the temptation to freeride when others are self-isolating. However, they deal with exponential growth poorly, as they only self-isolate sufficiently when lockdowns are imminent. Further, increased collective risk can motivate more self-isolation, even though the link between self-isolation and lockdowns is stochastic. Players underreport the influence of others’ choices on their own, and underestimate others’ self-isolation. We discuss implications for public health, and communication to the public.

Cooperative phenotype predicts climate change belief and pro-environmental behaviour

Understanding the psychological causes of variation in climate change belief and pro-environmental behaviour remains an urgent challenge for the social sciences. The “cooperative phenotype” is a stable psychological preference for cooperating in social dilemmas that involve a tension between individual and collective interest. Since climate change poses a social dilemma on a global scale, this issue may evoke similar psychological processes as smaller social dilemmas. Here, we investigate the relationships between the cooperative phenotype and climate change belief and behaviour with a representative sample of New Zealanders (N = 897). By linking behaviour in a suite of economic games to self-reported climate attitudes, we show robust positive associations between the cooperative phenotype and both climate change belief and pro-environmental behaviour. Furthermore, our structural equation models support a motivated reasoning account in which the relationship between the cooperative phenotype and pro-environmental behaviour is mediated by climate change belief. These findings suggest that common psychological mechanisms underlie cooperation in both micro-scale social dilemmas and larger-scale social dilemmas like climate change.

Analysis of Agricultural Biomass Energy Use and Greenhouse Gas Reduction Evidence from China

China is a large agricultural country, where agricultural activities and rural life cause a large amount of greenhouse gas (GHG) emissions. In the process of crop growth, production, and processing, a large number of crop straws and agricultural wasted products are produced, which become one of the important sources of biomass resources. However, few detailed studies focused on the potential of China's agricultural biomass energy conversion and carbon emission reduction, and fewer studies proposed GHG emission reduction strategies from the perspective of making full use of China's agricultural waste resources. In this study, the quantity calculation index of agricultural biomass energy was given, and the GHG emission reduction potential calculation index of agricultural biomass energy was constructed, with which the amount of GHG emissions caused by agricultural waste use in China was measured and the potential of GHG emission reduction caused by agricultural waste use would be easily speculated. Based on the statistical data of China, the quantity and GHG emission reduction potential of agricultural biomass resources in China in the recent 10 years (2009∼2018) were clarified. According to the research, the amount of agricultural waste equivalent to standard coal in China from 2009 to 2018 reached 280,0711 million tons. If all these resources were used to replace coal, a total of 4,474,483 million tons of carbon dioxide emissions could be saved. Assuming that these wastes are anaerobic, carbonized, or fully burned as fuel, CH₄ emissions could be reduced by up to 12.024 million tons and N₂O emissions by up to 185,000 tons. It can be seen that the effective utilization of agricultural biomass resources can replace coal, reduce backwardness such as land burning, and then reduce CO₂, CH₄, N₂O, and other greenhouse gas emissions, and promote the realization of carbon peak and carbon neutrality.

The Need for Sustainability, Equity, and International Exchange: Perspectives of Early Career Environmental Psychologists on the Future of Conferences

At the 2019 and 2021 International Conference on Environmental Psychology, discussions were held on the future of conferences in light of the enormous greenhouse gas emissions and inequities associated with conference travel. In this manuscript, we provide an early career researcher (ECR) perspective on this discussion. We argue that travel-intensive conference practices damage both the environment and our credibility as a discipline, conflict with the intrinsic values and motivations of our discipline, and are inequitable. As such, they must change. This change can be achieved by moving toward virtual and hybrid conferences, which can reduce researchers’ carbon footprints and promote equity, if employed carefully and with informal exchange as a priority. By acting collectively and with the support of institutional change, we can adapt conference travel norms in our field. To investigate whether our arguments correspond to views in the wider community of ECRs within environmental psychology, we conducted a community case study. By leveraging our professional networks and directly contacting researchers in countries underrepresented in those networks, we recruited 117 ECRs in 32 countries for an online survey in February 2022. The surveyed ECRs supported a change in conference travel practices, including flying less, and perceived the number of researchers wanting to reduce their travel emissions to be growing. Thirteen percent of respondents had even considered leaving academia due to travel requirements. Concerning alternative conference formats, a mixed picture emerged. Overall, participants had slightly negative evaluations of virtual conferences, but expected them to improve within the next 5 years. However, ECRs with health issues, facing visa challenges, on low funding, living in remote areas, with caretaking obligations or facing travel restrictions due to COVID-19 expected a switch toward virtual or hybrid conferences to positively affect their groups. Participants were divided about their ability to build professional relationships in virtual settings, but believed that maintaining relationships virtually is possible. We conclude by arguing that the concerns of ECRs in environmental psychology about current and alternative conference practices must be taken seriously. We call on our community to work on collective solutions and less travel-intensive conference designs using participatory methods.

Delegation to artificial agents fosters prosocial behaviors in the collective risk dilemma

Home assistant chat-bots, self-driving cars, drones or automated negotiation systems are some of the several examples of autonomous (artificial) agents that have pervaded our society. These agents enable the automation of multiple tasks, saving time and (human) effort. However, their presence in social settings raises the need for a better understanding of their effect on social interactions and how they may be used to enhance cooperation towards the public good, instead of hindering it. To this end, we present an experimental study of human delegation to autonomous agents and hybrid human-agent interactions centered on a non-linear public goods dilemma with uncertain returns in which participants face a collective risk. Our aim is to understand experimentally whether the presence of autonomous agents has a positive or negative impact on social behaviour, equality and cooperation in such a dilemma. Our results show that cooperation and group success increases when participants delegate their actions to an artificial agent that plays on their behalf. Yet, this positive effect is less pronounced when humans interact in hybrid human-agent groups, where we mostly observe that humans in successful hybrid groups make higher contributions earlier in the game. Also, we show that participants wrongly believe that artificial agents will contribute less to the collective effort. In general, our results suggest that delegation to autonomous agents has the potential to work as commitment devices, which prevent both the temptation to deviate to an alternate (less collectively good) course of action, as well as limiting responses based on betrayal aversion.

Motivating children's cooperation to conserve forests

Forests are essential common-pool resources. Understanding children's and adolescents' motivations for conservation is critical to improving conservation education. In 2 experiments, we investigated 1086 school-aged children and adolescents (6-16 years old) from China, the Democratic Republic of Congo, and the United States. testING participants in groups, we assessed their motivation for conservation based on collective-risk common-pool goods games in which they are threatened with losing their endowment unless the group donation exceeds a threshold needed to maintain the forest.eExtrinsic motivations, rather than intrinsic , tended to lead to successful cooperation to maintain a forest. Certainty of losing individual payoffs significantly boosted successful cooperative conservation efforts across cultures (success rates were 90.63 % and 74.19% in the 2 risk-extrinsic conditions and 43.75% in the control condition). In U.S. participants, 2 extrinsic incentives, priming discussions of the value of forests and delay of payoffs as punishment , also increased success of cooperative conservation (success rates were 97.22% and 76.92% in the 2 extrinsic-incentive conditions and 29.19% and 30.77% in the 2 control conditions). Conservation simulations, like those we used, may allow educators to encourage forest protection by leading groups to experience successful cooperation and the extrinsic incentives needed to motivate forest conservation. This article is protected by copyright. All rights reserved.

Effectiveness of environmental health and loss framing on household pharmaceutical take-back schemes

Pharmaceutical pollution poses an emerging environmental and public health problem. Together with increasing medicine use and pharmaceutical manufacturing effluents, improper disposal of household pharmaceutical waste significantly adds to this issue, despite pharmaceutical take-back schemes having been established in many countries. Even where take-back schemes are available return rates remain low. Previous studies have used only survey and interview methodologies and therefore merely described the situation. This study goes further, exploring not only the effects of the availability of information on pharmaceutical take-back schemes but also the effects of the framing of information provided to individuals on their intentions and reported behaviours to collect unused and/or expired household pharmaceuticals and return them to a pharmacy. The data were collected throughout three preregistered, randomised experiments with representative samples (N = 3754). The results show that tapping into individuals' pre-existing conception of the problem and psychological biases through the delivery of environmental health, loss framing information highly increased the odds of returning household pharmaceutical waste. This result is long-lasting (Studies 2 and 3), is found in various European countries (Study 1), and remains robust in all studies. Based on the results, we suggest that, in the context of household pharmaceutical waste management, psychologically informed, proactive approaches combined with targeted local action and services can reduce the psychological and practical barriers to pro-health and pro-environmental behaviour. The findings are used to support a policy recommendation that is cost-efficient, easy to use, and effective.