Analyzing evolutionary game theory in epidemic management: A study on social distancing and mask-wearing strategies.

When combating a respiratory disease outbreak, the effectiveness of protective measures hinges on spontaneous shifts in human behavior driven by risk perception and careful cost-benefit analysis. In this study, a novel concept has been introduced, integrating social distancing and mask-wearing strategies into a unified framework that combines evolutionary game theory with an extended classical epidemic model. To yield deeper insights into human decision-making during COVID-19, we integrate both the prevalent dilemma faced at the epidemic's onset regarding mask-wearing and social distancing practices, along with a comprehensive cost-benefit analysis. We explore the often-overlooked aspect of effective mask adoption among undetected infectious individuals to evaluate the significance of source control. Both undetected and detected infectious individuals can significantly reduce the risk of infection for non-masked individuals by wearing effective facemasks. When the economical burden of mask usage becomes unsustainable in the community, promoting affordable and safe social distancing becomes vital in slowing the epidemic's progress, allowing crucial time for public health preparedness. In contrast, as the indirect expenses associated with safe social distancing escalate, affordable and effective facemask usage could be a feasible option. In our analysis, it was observed that during periods of heightened infection risk, there is a noticeable surge in public interest and dedication to complying with social distancing measures. However, its impact diminishes beyond a certain disease transmission threshold, as this strategy cannot completely eliminate the disease burden in the community. Maximum public compliance with social distancing and mask-wearing strategies can be achieved when they are affordable for the community. While implementing both strategies together could ultimately reduce the epidemic's effective reproduction number ([Formula: see text]) to below one, countries still have the flexibility to prioritize either of them, easing strictness on the other based on their socio-economic conditions.

Evolutionary Game Dynamics with Environmental Feedback in a Network with Two Communities.

Recent developments of eco-evolutionary models have shown that evolving feedbacks between behavioral strategies and the environment of game interactions, leading to changes in the underlying payoff matrix, can impact the underlying population dynamics in various manners. We propose and analyze an eco-evolutionary game dynamics model on a network with two communities such that players interact with other players in the same community and those in the opposite community at different rates. In our model, we consider two-person matrix games with pairwise interactions occurring on individual edges and assume that the environmental state depends on edges rather than on nodes or being globally shared in the population. We analytically determine the equilibria and their stability under a symmetric population structure assumption, and we also numerically study the replicator dynamics of the general model. The model shows rich dynamical behavior, such as multiple transcritical bifurcations, multistability, and anti-synchronous oscillations. Our work offers insights into understanding how the presence of community structure impacts the eco-evolutionary dynamics within and between niches.

Regulatory mechanism of vulnerability disclosure behavior considering security crowd-testing: An evolutionary game analysis.

The security crowd-testing regulatory mechanism is a vital means to promote collaborative vulnerability disclosure. However, existing regulatory mechanisms have not considered multi-agent responsibility boundaries and stakeholders' conflicts of interest, leading to their dysfunction. Distinguishing from previous research on the motivations and constraints of ethical hacks' vulnerability disclosure behaviors from a legal perspective, this paper constructs an evolutionary game model of SRCs, security researchers, and the government from a managerial perspective to propose regulatory mechanisms promoting tripartite collaborative vulnerability disclosure. The results show that the higher the initial willingness of the three parties to choose the collaborative strategy, the faster the system evolves into a stable state. Regarding the government's incentive mechanism, establishing reward and punishment mechanisms based on effective thresholds is essential. However, it is worth noting that the government has an incentive to adopt such mechanisms only if it receives sufficient regulatory benefits. To further facilitate collaborative disclosure, Security Response Centers (SRC) should establish incentive mechanisms including punishment and trust mechanisms. Additionally, publicity and training mechanisms for security researchers should be introduced to reduce their revenue from illegal participation, which promotes the healthy development of security crowd-testing. These findings contribute to improving SRCs' service quality, guiding security researchers' legal participation, enhancing the government's regulatory effectiveness, and ultimately establishing a multi-party collaborative vulnerability disclosure system.

Promoting distributed photovoltaic adoption: An evolutionary game model approach for stakeholder coordination.

Distributed photovoltaic (DPV) is a promising solution to climate change. However, the widespread adoption of DPV faces challenges, such as high upfront costs, regulatory barriers, and market uncertainty. Addressing these barriers requires coordinating the interests of stakeholders in the promotion of DPV. Therefore, this paper constructs a three-party evolutionary game model in a social network with the government, investment companies and residents as the main subjects and examines the influence of different subjects' behavioral strategies on the promotion of DPV under the social learning mechanism. The results show that: (1) In the game equilibrium, both the government and residents hold a positive attitude towards the promotion of DPV; (2) Companies will obtain most of the subsidies through market power and information differences, resulting in the increase of government subsidies that do not always benefit residents; (3) The increase of energy consumption and pollution prevention costs can promote companies' investment in DPV; (4) The increase of environmental protection taxes to a certain extent helps companies to take responsibility for promoting DPV, reducing the pressure on the government to promote it and increasing residents' income. This study provides insights into the sustainable development of DPV.

Migration costs and rewarding schemes in spatial public goods games.

This study explores the influence of migration costs and rewarding schemes on cooperation through the implementation of computational behavioral models in spatial public goods games. The former involves a cost for agents to migrate to a neighboring group, while the latter rewards them for remaining in the same group for multiple rounds. By analyzing these mechanisms separately and in combination, we unveil their effects on cooperative behavior. The grid-based game dynamics begins with equal size groups, and agents can adjust their contributions each round, with the option to migrate if unsatisfied. Our findings reveal that when considered separately, the rewarding scheme is not as effective in achieving full cooperation as the migration cost scheme. Combining migration costs and rewards instead yields high cooperation levels with low public goods game enhancement factors and migration probability. Our results offer valuable insights for contexts where promoting cooperative behavior is crucial, such as community engagement development and public policies.

An innovative fractional-order evolutionary game theoretical study of personal protection, quarantine, and isolation policies for combating epidemic diseases.

This study uses imposed control techniques and vaccination game theory to study disease dynamics with transitory or diminishing immunity. Our model uses the ABC fractional-order derivative mechanism to show the effect of non-pharmaceutical interventions such as personal protection or awareness, quarantine, and isolation to simulate the essential control strategies against an infectious disease spread in an infinite and uniformly distributed population. A comprehensive evolutionary game theory study quantified the significant influence of people's vaccination choices, with government forces participating in vaccination programs to improve obligatory control measures to reduce epidemic spread. This model uses the intervention options described above as a control strategy to reduce disease prevalence in human societies. Again, our simulated results show that a combined control strategy works exquisitely when the disease spreads even faster. A sluggish dissemination rate slows an epidemic outbreak, but modest control techniques can reestablish a disease-free equilibrium. Preventive vaccination regulates the border between the three phases, while personal protection, quarantine, and isolation methods reduce disease transmission in existing places. Thus, successfully combining these three intervention measures reduces epidemic or pandemic size, as represented by line graphs and 3D surface diagrams. For the first time, we use a fractional-order derivate to display the phase-portrayed trajectory graph to show the model's dynamics if immunity wanes at a specific pace, considering various vaccination cost and effectiveness settings.

Game-theoretic agent-based modelling of micro-level conflict: Evidence from the ISIS-Kurdish war.

This article delves into the dynamics of a dyadic political violence case study in Rojava, Northern Syria, focusing on the conflict between Kurdish rebels and ISIS from January 1, 2017, to December 31, 2019. We employ agent-based modelling and a formalisation of the conflict as an Iterated Prisoner's Dilemma game. The study provides a nuanced understanding of conflict dynamics in a highly volatile region, focusing on microdynamics of an intense dyadic strategic interaction between two near-equally- powered actors. The choice of using a model based on the Iterated Prisoner's Dilemma, though a classical approach, offers substantial insights due to its ability to model dyadic, equally-matched strategic interactions in conflict scenarios effectively. The investigation primarily reveals that shifts in territorial control are more critical than geographical or temporal factors in determining the conflict's course. Further, the study observes that the conflict is characterised by periods of predominantly one-sided violence. This pattern underscores that the distribution of attacks, and target choices are a more telling indicator of the conflict nature than specific behavioural patterns of the actors involved. Such a conclusion aligns with the strategic implications of the underlying model, which emphasises the outcome of interactions based on differing aggression levels. This research not only sheds light on the conflict in Rojava but also reaffirms the relevance of this type of game-theoretical approach in contemporary conflict analysis.

An evolutionary game-theoretic analysis of the "multi-agent co-governance" system of unfair competition on internet platforms.

The increasingly prominent issue of unfair competition on Internet platforms (IPUC) severely restricts the healthy and sustainable development of the platform economy. Based on the IPUC "multi-agent co-governance" scenario, this paper introduces stochastic disturbances and continuous strategy set to improve the classical binary deterministic evolutionary game system. The results show that after considering stochastic disturbances, the positive state corresponding to the equilibrium point (1,1) is no longer stable, and the required parameter conditions are more stringent. The IPUC "multi-agent co-governance" system under stochastic disturbances exhibits specific vulnerability. In the continuous strategy set evolutionary game system, government departments and Internet platforms can flexibly make optimal decisions based on maximizing expected returns, and strategy selection has better elasticity. Regardless of the evolutionary game scenario, maintaining the participation level of NGOs and the public above a certain threshold while increasing the penalty intensity is conducive to the evolution of the game system toward the positive state. The analysis process and conclusions provide insights and guidance for the governments to design the IPUC regulatory system and frameworks.

The economic impacts of social activism and corporate social responsibility on food fraud.

The study examines the relationship between the corporate social responsibility (CSR) investments of a food firm, an activist's incentive to target the firm to uncover and deter fraudulent behavior, and the firm's incentive to commit food fraud. Specifically, we develop a game theoretic model to analyze the strategic interaction between a food firm that decides whether to provide a credence food attribute and whether to misrepresent the quality of its product, and an activist who decides whether to monitor the firm and launch a campaign to uncover and remove false/misleading quality claims. We further examine the effect of CSR and the activist's presence on the level of quality the firm provides. We derive the conditions under which an activist will find it optimal to monitor the firm to uncover fraudulent quality claims and the firm will find it optimal to misrepresent its product quality. Analytical results show that the greater the firm's CSR investments, the less likely it is that the activist will find it optimal to monitor the firm, and the more likely it is that the firm will find it optimal to misrepresent its product quality. Results also show that the firm is more likely to misrepresent its product quality when its effectiveness in contesting the activist's campaign is relatively high, and more likely to actually provide a high-quality product when the cost of the credence attribute is relatively low.

Advanced optimal tracking integrating a neural critic technique for asymmetric constrained zero-sum games.

This paper investigates the optimal tracking issue for continuous-time (CT) nonlinear asymmetric constrained zero-sum games (ZSGs) by exploiting the neural critic technique. Initially, an improved algorithm is constructed to tackle the tracking control problem of nonlinear CT multiplayer ZSGs. Also, we give a novel nonquadratic function to settle the asymmetric constraints. One thing worth noting is that the method used in this paper to solve asymmetric constraints eliminates the strict restriction on the control matrix compared to the previous ones. Further, the optimal controls, the worst disturbances, and the tracking Hamilton-Jacobi-Isaacs equation are derived. Next, a single critic neural network is built to estimate the optimal cost function, thus obtaining the approximations of the optimal controls and the worst disturbances. The critic network weight is updated by the normalized steepest descent algorithm. Additionally, based on the Lyapunov method, the stability of the tracking error and the weight estimation error of the critic network is analyzed. In the end, two examples are offered to validate the theoretical results.

Safe Food Supply Chain as Health Network: An Evolutionary Game Analysis of Behavior Strategy for Quality Investment.

There is a natural relation between human health and the quality of their food and drinks, and elevating the quality input level of food production for all enterprises within the food supply chain system forms the foundation for preventing various potential food safety risks that may be encountered. Unlike the previous research on quality investment of food production by enterprises, this paper probes into the evolutionary routes of the behavior strategy selection of subjects in the food supply chain and the preconditions for the equilibrium points of the social co-governance system. It takes the approach of establishing a tripartite evolutionary game model of food suppliers, food manufacturers and consumers on the basis of the social co-governance framework, in view of the above, this paper focuses on the influence of the reputation mechanism and the market contracts among supply chain subjects on the selection of a behavior strategy for quality investment by enterprises under the condition of lawful regulation by government. The results show that every subject selects their own behavior strategy on the basis of the balance of their respective interests. The net disbursement incurred by enterprises for quality investment and the costs of participation in governance by consumers constitute the dominant factors that influence both enterprises' selection of a behavior strategy and the level of social co-governance. Compared with the increase in economic punishment imposed on suppliers for production of risky food raw materials, it is more efficient to control food safety risks by lowering the costs of quality investment by suppliers. Accordingly, this paper proposes advice on policy in an attempt to provide inspiration for preventing and controlling food safety risks.

Smart transition pathways and development incentive mechanism of China's smart community elderly care industry under market dominance: Considering a multi-subjective behavior game.

Against the backdrop of an aging population, China is actively experimenting with an innovative elderly care model, so smart community elderly care has recently received widespread attention. However, the results of the implementation of the model have not yet met the expectation due to the variety of interests among the relevant participants. In this study, we identified the most core stakeholders in smart community elderly care, developed a four-party evolutionary game model including local governments, communities, service supply enterprises and households with elderly members. By applying the system dynamics method, we simulate the evolutionary paths and explore the complex interactions at the multiparticipant level in order to facilitate the transition of community elderly care services from traditional to smart, and then propose managerial insights for accelerating the construction of smart community elderly care. The results suggest that: (1) the four players in the game influence each other and are intimately related, and the benign interaction between them will further stimulate the vitality of the smart community elderly care industry; (2) appropriate improvement in policy support will strongly promote smart community elderly care, and the incentive effect on the demand side (households with elderly members) is more significant; (3) when households' preference for smart services increases, and the perceived value to communities and enterprises reaches a certain threshold, communities and enterprises will actively adopt smart solution and technology as well as develop stable portfolio strategy; (4) measures such as simultaneously increasing the level of smart and resource synergy will promote the system evolution toward smart services, and the system is more sensitive to the internal behavior of the enterprise than the external behavior between community and enterprise.

The Unification of Evolutionary Dynamics through the Bayesian Decay Factor in a Game on a Graph.

We unify evolutionary dynamics on graphs in strategic uncertainty through a decaying Bayesian update. Our analysis focuses on the Price theorem of selection, which governs replicator(-mutator) dynamics, based on a stratified interaction mechanism and a composite strategy update rule. Our findings suggest that the replication of a certain mutation in a strategy, leading to a shift from competition to cooperation in a well-mixed population, is equivalent to the replication of a strategy in a Bayesian-structured population without any mutation. Likewise, the replication of a strategy in a Bayesian-structured population with a certain mutation, resulting in a move from competition to cooperation, is equivalent to the replication of a strategy in a well-mixed population without any mutation. This equivalence holds when the transition rate from competition to cooperation is equal to the relative strength of selection acting on either competition or cooperation in relation to the selection differential between cooperators and competitors. Our research allows us to identify situations where cooperation is more likely, irrespective of the specific payoff levels. This approach provides new perspectives into the intended purpose of Price's equation, which was initially not designed for this type of analysis.

The impact of mobility costs on cooperation and welfare in spatial social dilemmas.

From over-exploitation of resources to urban pollution, sustaining well-being requires solving social dilemmas of cooperation. Often such dilemmas are studied assuming that individuals occupy fixed positions in a network or lattice. In spatial settings, however, agents can move, and such movements involve costs. Here we investigate how mobility costs impact cooperation dynamics. To this end, we study cooperation dilemmas where individuals are located in a two-dimensional space and can be of two types: cooperators-or cleaners, who pay an individual cost to have a positive impact on their neighbours-and defectors-or polluters, free-riding on others' effort to sustain a clean environment. Importantly, agents can pay a cost to move to a cleaner site. Both analytically and through agent-based simulations we find that, in general, introducing mobility costs increases pollution felt in the limit of fast movement (equivalently slow strategy revision). The effect on cooperation of increasing mobility costs is non-monotonic when mobility co-occurs with strategy revision. In such scenarios, low (yet non-zero) mobility costs minimise cooperation in low density environments; whereas high costs can promote cooperation even when a minority of agents initially defect. Finally, we find that heterogeneity in mobility cost affects the final distribution of strategies, leading to differences in who supports the burden of having a clean environment.

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.

Research on multilateral collaboration strategies in agricultural seed quality assurance.

Seeds, as the initial products in agricultural systems, play a pivotal role in ensuring quality, fundamental to national food security and sustainable agricultural development. This study introduces a concept integrating public governance and evolutionary game theory to construct a quadripartite evolutionary game model involving seed companies, certification agencies, farmers, and governmental departments. It considers the strategic choices of these stakeholders under varying economic motivations and market mechanisms, as well as the influence of external regulation and incentives on game strategies. The existence conditions for evolutionarily stable strategy combinations are determined using the Lyapunov first method, and MATLAB is employed for numerical simulation analysis to validate the game analysis under initial conditions. The simulation results reveal two potential equilibrium points corresponding to different strategic choices among stakeholders. The study finds that producing high-quality seeds and the refusal of certification agencies to engage in rent-seeking are crucial for ensuring seed quality. Additionally, the cost-benefit ratio of seed companies, the speculative cost of certification agencies, and the rights-protection cost of farmers are key determinants in the evolution of seed quality assurance strategies. This research also holds practical significance in enhancing seed quality assurance mechanisms and fostering sustainable development in agriculture.

Tolerance for corruption and descriptive social norm: An experimental study of embezzlement.

Public tolerance for corruption within a society significantly influences the prevalence of corrupt practices, but less is known about how this tolerance evolves with social norms. This paper presents experimental evidences demonstrating that the descriptive social norm indicating widespread corruption can lead to increased tolerance for corruptive acts. We introduce an asymmetric information ultimatum game to simulate the interactions between embezzlers and citizens. Game theoretical analysis reveals that victims anticipating corruption will exhibit greater compliance with embezzlement when the offers are evaluated based on descriptive norms. To test the hypothesis, we employ a framing effect to induce variations in descriptive norms within a behavioral experiment. Although the treatment effect is significant only in the subgroup of student cadres, this subgroup demonstrated increased beliefs about embezzlement, greater tolerance for corruption, and a heightened propensity to embezzle when exposed to framings with hierarchical implications. This paper contributes to the corruption literature by examining the effects of descriptive norms on victims' responses to embezzlement. It offers a more comprehensive perspective on how social standards shape public opinions and corrupt actions, enhancing our understanding of the self-reinforcing nature of corruption.

Evolutionarily stable payoff matrix in hawk-dove games.

BACKGROUND: Classical matrix game models aim to find the endpoint of behavioural evolution for a set of fixed possible interaction outcomes. Here, we introduce an evolutionary model in which not only the players' strategies but also the payoff matrix evolves according to natural selection. RESULTS: We start out from the hawk-dove matrix game and, in a way that is consistent with the monomorphic model setup of Maynard Smith and Price, introduce an evolving phenotypic trait that quantifies fighting ability and determines the probability of winning and the cost of losing escalated hawk-hawk fights. We define evolutionarily stable phenotypes as consisting of an evolutionarily stable strategy and an evolutionarily stable trait, which in turn describes a corresponding evolutionarily stable payoff matrix. CONCLUSIONS: We find that the maximal possible cost of escalating fights remains constant during evolution assuming a separation in the time scales of fast behavioural and slow trait selection, despite the fact that the final evolutionarily stable phenotype maximizes the payoff of hawk-hawk fights. Our results mirror the dual nature of Darwinian evolution whereby the criteria of evolutionary success, as well as the successful phenotypes themselves, are a product of natural selection.

WIPO initiative of transforming traditional resources and sharing rights: An evolutionary game analysis and a Chinese context.

WIPO-GRTKF specifies, for the first time, how traditional resources embodied by traditional knowledge, genetic resources, and folklore can be defined, and what the relationship between original rights, and rights arising from the transformation and utilisation of traditional resources can be understood. Committed to promoting innovation, shared benefits and balanced interests, WIPO tries to achieve a balance between preventing users from violating holders' original rights through the acquisition of patent, trademark and copyright, and incentivizing all stakeholders to transform traditional resources to improve the greater good. The document triggers a new round of disputes among interest groups over how to share rights arising from the transformation and utilisation of traditional resources. Using an evolutionary game model to simulate how holders and users transform traditional resources, and share rights, we find that when the two sides choose to cooperate to apply for transformation and give consent to use, their benefits are maximised and strategies stabilised. We suggest that in the transforming process, holders' rights and users' interests be given equal emphasis, and an autonomous and open mode combining statutory licensing, and justified utilisation of original rights be employed. We advocate for a hybrid legislative arrangement that integrates the incentive of IPRs as private rights, and the safeguard of public rights. In the dual subject system, both users and holders enjoy multiple rights in the process of protecting and transforming traditional resources. The Chinese approach to transforming traditional resources and sharing their rights will contribute to sustainable development of traditional resource industry across the globe.

Game analysis on PPP model operation of abandoned mines ecological restoration under the innovation of central government's reward and punishment system in China.

There is a huge funding gap in the abandoned mines ecological restoration in China. It is of great research value to explore how PPP model can better introduce social capital into the low-profit ecological restoration of abandoned mines. Based on the innovation perspective of the central government's reward and punishment system, this paper constructs an evolutionary game model of "local government-social capital", analyzes the interaction and behavior mechanism of core stakeholders in the operation process of abandoned mines ecological restoration PPP mode, and discusses the influence of evolutionary equilibrium strategy and parameters change on evolutionary strategy under different scenarios by Matlab simulation. The research shows that the abandoned mines ecological restoration needs the support of the central government. When the local government lightly punishes the low-quality service of social capital, the central government needs to pay higher costs to promote all parties to actively participate in the operation and supervision of the PPP project. The revenue and cost of government supervision, the operating subsidy for social capital and the cost saved by social capital in providing bad service are the key factors affecting the evolution of the game between government and social capital. Punishment can effectively spur social capital to keep the contract and operate in the project, but the punishment effect will be ineffective without government supervision. Finally, some suggestions are put forward, such as establishing a long-term supervision mechanism and a reasonable income mechanism for PPP projects, increasing penalties for violations, attracting third parties to reduce supervision costs and strengthening communication between the two parties, so as to make the project take into account the economic performance of social capital and the social welfare of government departments, and achieve dual Pareto improvement.