Search

The competition between platforms supported by digital technology, to a great extent, affects the structure of the whole industry and the fate of individual enterprises in the industry. For related enterprises, it is very important to clarify the influencing factors of platform competition equilibrium. This paper constructs a game model that includes platforms, suppliers, and the final consumers. We analyze the condition and stability of each equilibrium and the impacts of the characteristics of the core and complementary products on the equilibrium by using the method of evolutionary game. Our results show the following: (1) If the two platforms initially have separate advantages in terms of the number of suppliers or consumers, there will be an equilibrium of the coexistence of the two platforms; otherwise, there will be an equilibrium of single platform dominating. (2) The equilibrium of a single platform dominating is more stable than that of the coexistence of multiple platforms. (3) The equilibrium of coexistence is more easily broken by the occasional shock of increasing or decreasing the number of suppliers than by consumers. (4) Platforms with poor core product quality and a high price for core and complementary products can coexist with other superior platforms only if the former has more consumers and suppliers at the beginning of the competition. This paper not only enriches the research content in the field of platform competition, but also provides new ideas for them to develop appropriate competition strategies in combination with their own conditions. Plain Language Summary: The Evolutionary Game of Platform Competition The purpose of this paper is to analyze the equilibrium state of platform competition in a dynamic market from a tripartite perspective of platform-supplier-consumer. This paper constructs a game model that includes platforms, suppliers, and the final consumers. We analyze the condition and stability of each equilibrium and the impacts of the characteristics of the core and complementary products on the equilibrium by using the method of evolutionary game. Our results show the following: (1) If the two platforms initially have separate advantages in terms of the number of suppliers or consumers, there will be an equilibrium of the coexistence of the two platforms; otherwise, there will be an equilibrium of single platform dominating. (2) The equilibrium of a single platform dominating is more stable than that of the coexistence of multiple platforms. (3) The equilibrium of coexistence is more easily broken by the occasional shock of increasing or decreasing the number of suppliers than by consumers. (4) Platforms with poor core product quality and a high price for core and complementary products can coexist with other superior platforms only if the former has more consumers and suppliers at the beginning of the competition. This paper not only enriches the research content in the field of platform competition, but also provides new ideas for them to develop appropriate competition strategies in combination with their own conditions. The limitation of this paper is that it does not consider the possibility of having companies enter or exit the industry. [ABSTRACT FROM AUTHOR]

Background: China has continuously issued policies to speed up the interconnection, mutual recognition, sharing of medical information systems, and data integration management across regions and institutions. However, the vertical integration of electronic health records (EHRs) within the medical consortium is hampered by "poor mechanism and insufficient motivation" and the phenomenon of "free riding" among participating medical institutions, which makes the integration less effective. Objective: We hope to clarify the game mechanism of stakeholders in the vertical integration of EHRs, and put forward targeted policy suggestions for improvement. Methods: We constructed the "government-hospital-patient" tripartite evolutionary game model based on the detailed analysis of the research problems and their assumptions. We then simulated the game strategies and outcomes of each participant using the system dynamics approach to reveal the long-term strategy evolution mechanism of the core participants in the vertical integration of EHRs in the medical consortium, as well as the influencing factors and action mechanisms of each party's strategy evolution to provide references for improving relevant policies. Results: The evolutionary game system could eventually reach an optimal equilibrium, but in areas where the government was required to be in a dominant position, patient supervision was necessary to have a positive role, while a reasonable reward and punishment mechanism can promote active participation of hospitals. Conclusions: The effective way to achieve the goal of vertical integration of EHRs in the medical consortium is to build a multiagent coordination mechanism under the guidance of the government. Meanwhile, it is necessary to establish a scientific integration performance evaluation mechanism, a reward and punishment mechanism, and a benefit distribution mechanism to promote the healthy development of vertical integration of EHRs in medical consortiums. [ABSTRACT FROM AUTHOR]

Major infrastructure projects (MIPs) possess significant strategic positions in the national economy and social development. However, recently, the rent-seeking behavior between supervision units and project contractors has intensi- fied in project construction. This paper aims to study the behavior decision-making of stakeholders in rent-seeking behavior supervision system of MIPs. In the complex and uncertain environment of MIPs, game players have cognitive bias and value perception preference. Therefore, this study introduced prospect theory and constructed the perceived return matrix and evolutionary game model of MIP rent-seeking behavior supervision among project owners, supervision units, and project contractors. From the perspective of risk perception theory, the reasons for the behavioral tendencies of game participants and the conditions for the steady state of strategy selection were explored through system dynamics simulations. The results showed that the stable state of the optimal strategy in the rent-seeking behavior supervision system of MIPs is related to the cognitive bias of the game players and is influenced by the level of regulation cost, the intensity of punishment and the size of accident losses. The contribution of this study lies in providing theoretical basis and decision support for constructing a long-term preventive mechanism for rent-seeking activities in MIPs. [ABSTRACT FROM AUTHOR]

A new wave of protectionism is threatening the open and cooperative international order. This paper applies evolutionary game theory to analyze the stability of international trade cooperation. Global trade liberalization is modeled as an iterated prisoner's dilemma between all possible pairs of WTO member states. Empirical data are used to model the sizes and competitiveness of the respective markets, which then determine the resulting gains and costs of trade cooperation. Because of the large number of WTO member states and repeated rounds of their interactions, we use computer simulations to calculate the strategies that lead to the maximum 'fitness' of the respective member states and consequently diffuse through the population of countries. The results of our simulations show that international trade cooperation is not a stable equilibrium and that extreme levels of trade liberalization can be exploited successfully by protectionist trade policies. [ABSTRACT FROM AUTHOR]

In the midst of the COVID-19 pandemic, with limited or no supplies of vaccines and treatments, people and policymakers seek easy to implement and cost-effective alternatives to combat the spread of infection during the pandemic. The practice of wearing a mask, which requires change in people's usual behavior, may reduce disease transmission by preventing the virus spread from infectious to susceptible individuals. Wearing a mask may result in a public good game structure, where an individual does not want to wear a mask but desires that others wear it. This study develops and analyzes a new intervention game model that combines the mathematical models of epidemiology with evolutionary game theory. This approach quantifies how people use mask-wearing and related protecting behaviors that directly benefit the wearer and bring some advantage to other people during an epidemic. At each time-step, a suspected susceptible individual decides whether to wear a facemask, or not, due to a social learning process that accounts for the risk of infection and mask cost. Numerical results reveal a diverse and rich social dilemma structure that is hidden behind this mask-wearing dilemma. Our results highlight the sociological dimension of mask-wearing policy. [ABSTRACT FROM AUTHOR]

The spreading of cooperation in structured population is a challenging problem which can be observed at different scales of social and biological organization. Generally, the problem is studied by evaluating the chances that few initial invading cooperators, randomly appearing in a network, can lead to the spreading of cooperation. In this paper we demonstrate that in many scenarios some cooperators are more influential than others and their initial positions can facilitate the spreading of cooperation. We investigate six different ways to add initial cooperators in a network of cheaters, based on different network-based measurements. Our research reveals that strategically positioning the initial cooperators in a population of cheaters allows to decrease the number of initial cooperators necessary to successfully seed cooperation. The strategic positioning of initial cooperators can also help to shorten the time necessary for the restoration of cooperation. The optimal ways in which the initial cooperators should be placed is, however, non-trivial in that it depends on the degree of competition, the underlying game, and the network structure. Overall, our results show that, in structured populations, few cooperators, well positioned in strategically chosen places, can spread cooperation faster and easier than a large number of cooperators that are placed badly. [ABSTRACT FROM AUTHOR]

In various types of structured communities newcomers choose their interaction partners by selecting a role-model and copying their social networks. Participants in these networks may be cooperators who contribute to the prosperity of the community, or cheaters who do not and simply exploit the cooperators. For newcomers it is beneficial to interact with cooperators but detrimental to interact with cheaters. However, cheaters and cooperators usually cannot be identified unambiguously and newcomers' decisions are often based on a combination of private and public information. We use evolutionary game theory and dynamical networks to demonstrate how the specificity and sensitivity of those decisions can dramatically affect the resilience of cooperation in the community. We show that promiscuous decisions (high sensitivity, low specificity) are advantageous for cooperation when the strength of competition is weak; however, if competition is strong then the best decisions for cooperation are risk-adverse (low sensitivity, high specificity). Opportune decisions based on private and public information can still support cooperation but suffer of the presence of information cascades that damage cooperation, especially in the case of strong competition. Our research sheds light on the way the interplay of specificity and sensitivity in individual decision-making affects the resilience of cooperation in dynamical structured communities. [ABSTRACT FROM AUTHOR]

Cooperation is a relevant and controversial phenomenon in human societies. Indeed, although it is widely recognized essential for tackling social dilemmas, finding suitable policies for promoting cooperation can be arduous and expensive. More often, it is driven by pre-established schemas based on norms and punishments. To overcome this paradigm, we highlight the interplay between the influence of social interactions on networks and spontaneous self-regulating mechanisms on individuals behavior. We show that the presence of these mechanisms in a prisoner's dilemma game, may oppose the willingness of individuals to defect, thus allowing them to behave cooperatively, while interacting with others and taking conflicting decisions over time. These results are obtained by extending the Evolutionary Game Equations over Networks to account for self-regulating mechanisms. Specifically, we prove that players may partially or fully cooperate whether self-regulating mechanisms are sufficiently stronger than social pressure. The proposed model can explain unconditional cooperation (strong self-regulation) and unconditional defection (weak self-regulation). For intermediate self-regulation values, more complex behaviors are observed, such as mutual defection, recruiting (cooperate if others cooperate), exploitation of cooperators (defect if others cooperate) and altruism (cooperate if others defect). These phenomena result from dynamical transitions among different game structures, according to changes of system parameters and cooperation of neighboring players. Interestingly, we show that the topology of the network of connections among players is crucial when self-regulation, and the associated costs, are reasonably low. In particular, a population organized on a random network with a Scale-Free distribution of connections is more cooperative than on a network with an Erdös-Rényi distribution, and, in turn, with a regular one. These results highlight that social diversity, encoded within heterogeneous networks, is more effective for promoting cooperation. [ABSTRACT FROM AUTHOR]

This article revisits the 'race to the bottom' in international labour law, in light of new developments in evolutionary and epistemic game theory and considering new empirical findings on the economic effects of labour rights. Accordingly, it explores two solutions to this collective action problem not previously analysed in labour law literature—'indeterminate play' and the 'correlating device'—and it shows how these solutions relate to international trade law and international labour law. Moreover, a new perspective is offered, according to which international labour law and international trade law can be complementary in fostering global co-operation on labour regulation and in supporting development efforts. Through a novel characterisation of global labour governance according to three game theoretical models, this study ultimately highlights the importance of freedom of association and collective bargaining in enhancing co-operation among states and promoting processes by which countries' social and economic development can be incrementally raised. [ABSTRACT FROM AUTHOR]

The identification of the most influential individuals in structured populations is an important research question, with many applications across the social and natural sciences. Here, we study this problem in evolutionary populations on static networks, where invading cheaters can lead to the collapse of cooperation. We propose six strategies to rank the invading cheaters and identify those which mostly facilitate the collapse of cooperation. We demonstrate that the type of successful rankings depend on the selection strength, the underlying game, and the network structure. We show that random ranking has generally little ability to successfully identify invading cheaters, especially for the stag-hunt game in scale-free networks and when the selection strength is strong. The ranking based on degree can successfully identify the most influential invaders when the selection strength is weak, while more structured rankings perform better at strong selection. Scale-free networks and strong selection are generally detrimental to the performance of the random ranking, but they are beneficial for the performance of structured rankings. Our research reveals how to identify the most influential invaders using statistical measures in structured communities, and it demonstrates how their success depends on population structure, selection strength, and on the underlying game dynamics. [ABSTRACT FROM AUTHOR]

Leadership can be effective in promoting cooperation within a group, but as the saying goes "heavy is the head that wears the crown". A lot of debate still surrounds exactly what motivates individuals to expend the effort necessary to lead their groupmates. Evolutionary game theoretic models represent individual's thought processes by strategy update protocols. The most common of these are random mutation, individual learning, selective imitation, and myopic optimization. Recently we introduced a new strategy update protocol - foresight - which takes into account future payoffs, and how groupmates respond to one's own strategies. Here we apply our approach to a new 2 × 2 game, where one player, a leader, ensures via inspection and punishment that the other player, a subordinate, produces collective good. We compare the levels of inspection and production predicted by Nash Equilibrium, Quantal Response Equilibrium, level-k cognition, fictitious play, reinforcement learning, selective payoff-biased imitation, and foresight. We show that only foresight and selective imitation are effective at promoting contribution by the subordinate and inspection and punishment by the leader. The role of selective imitation in cultural and social evolution is well appreciated. In line with our prior findings, foresight is a viable alternative route to cooperation. [ABSTRACT FROM AUTHOR]

'Pollination syndromes' involving floral nectar have eluded satisfactory evolutionary explanation. For example, floral nectars for vertebrate-pollinated plants average low sugar concentrations, while such animals prefer high concentrations, perplexing pollination biologists and arousing recent controversy. Such relationships should result from evolutionary games, with plants and pollinators adopting Evolutionarily Stable Strategies, and nectar manipulating rather than attracting pollinators. Plant potential to manipulate pollinators depends on relationships between neighbouring flowers within plants, for all nectar attributes, but this has not been investigated. We measured nectar volume, concentration and sugar composition for open flowers on naturally-growing Blandfordia grandiflora plants, presenting classic bird-pollinated plant syndrome. To evaluate potential pollinator manipulation through nectar, we analysed relationships between neighbouring flowers for nectar volume, concentration, proportion sucrose, log(fructose/glucose), and sugar weight. To evaluate potential attraction of repeat-visits to flowers or plants through nectar, we compared attributes between successive days. Nearby flowers were positively correlated for all attributes, except log(fructose/glucose) as fructose≈glucose. Most relationships between nectar attributes for flowers and plants on successive days were non-significant. Nectar-feeding pollinators should therefore decide whether to visit another flower on a plant, based on all attributes of nectar just-obtained, enabling plants to manipulate pollinators through adjusting nectar. Plants are unlikely to attract repeat pollinator-visits through nectar production. Floral nectar evolution is conceptually straightforward but empirically challenging. A mutant plant deviating from the population in attributes of nectar-production per flower would manipulate, rather than attract, nectar-feeding pollinators, altering pollen transfer, hence reproduction. However, links between floral nectar and plant fitness present empirical difficulties. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Southeast University (English Edition) is the property of Journal of Southeast University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper combines evolutionary game theory and input–output analysis to assess firms' strategic location choice. To evaluate the model, firms competed in the automotive sector of Mercosur. To decide where to locate, the following exogenous factors were considered: potential market; local productive interdependence; tax incentive; and macroeconomic stability. Firms assigned weights to these factors in their location decision. It was found that competing in a market where there is tax exemption is not always an ideal location decision, contradicting the common-sense assumption by which there is a direct relationship between government incentives and the attractiveness of regions. [ABSTRACT FROM AUTHOR]

Early occupation at Nixtun-Ch'ich', on the western edge of Lake Petén Itzá, is dated by two ceramic complexes, K'as and Chich. These represent the Late and Terminal Early Preclassic or the early and late "Pre-Mamom" periods, respectively (ca. 1300–800 BC), including a "Transitional" period incorporating Nix Middle Preclassic (Mamom) pottery. Comparisons with complexes at other sites in the region permit the dating of 10 construction loci, including 3 in the civic-ceremonial core. Low late Pre-Mamom platforms were raised and expanded in Transitional and Early Middle Preclassic times, when they were elaborated into two E-Groups and a Triadic Structure on the central axis. This building activity is interpreted in terms of cooperative or corporate labor organization and related to evolutionary game theory. The ritual foundation of such organization is evident in the site's gridded layout based on a mythical world-creation crocodile. [ABSTRACT FROM AUTHOR]

Controlling environmental pollution efficiently has become the common goal of the entire society. To explore whether the strategy of environmental pollution prevention and control formulated by the central government can effectively prevent the failure of traditional environmental regulation, the central and local governments were selected as the participants of a game model. The incentive mechanism was introduced into the constraints, the evolutionary game model of governments and enterprises was established, and the optimal regulation strategy of both sides was constructed from the effect of environmental pollution prevention and control. Results show that the key to preventing the failure of pollution control strategies is to introduce the constraints of the central government, allocate the cost of pollution control, and provide financial support for the prevention and control of environmental pollution. In addition, the central and local governments should adopt different prevention strategies. The optimal allocation strategy of the special funds for environmental pollution prevention and control at the central government level should be to correlate positively the amount of funds with the amount declared by the local government and show a marginal decreasing relationship. Local governments should not impose severe penalties on enterprises for excess discharge of pollutants. With the escalating discharge, imposing reasonable environmental taxes and reducing the marginal emission reduction costs of enterprises are better regulation means than increasing penalties. [ABSTRACT FROM AUTHOR]

We analyze cooperation of individuals in a family context, using a Public Good game. In a lab experiment, 165 individuals from 55 three-generation families (youth, parent, and grandparent) play a repeated Public Good game in three different treatments: one in which three members of the same family play each other (family), a second with the youth and two non-family members, while preserving the previous generational structure (inter-generational), and a third in which three randomly-selected players play each other (random). We find that all the age groups cooperate more when playing with relatives, indicating that family ties may have a positive relationship to contributions to the Public Good. We also find that this trend is more evident for the youths and the parents than for the grandparents. Furthermore, young individuals tend to cooperate less than older generations, especially in non-family treatments. Our results serve as evidence of the relationship between family ties and inter-generational cooperative behaviors. [ABSTRACT FROM AUTHOR]

Abstract In social networks, information diffusion is affected by network topology and driving factors. In this work, we investigate the structure of networks, map networks into multidimensional network space, and apply user social behavioral and psychological features to social networks. First, by exploring the network topological structure, we map it into three network spaces: behavior influence, attribute influence, and topological influence subnets. With a hierarchical process, the coupling relationship among the subnets can be reduced, and we can analyze the effect of the driving factors of each subnet on information diffusion separately. Second, assuming that the psychological characteristics of topic users are the driving factors affecting information diffusion, the concept of topic heat is defined. On the basis of evolutionary game theory, a dynamic evolution strategy of user behavior is proposed. In this way, we can explore the effect of a user's psychological game on information diffusion. Finally, on the basis of the traditional Susceptible–Infected–Recovered (SIR) model, the improved diffusion model is obtained by combining the network topology with the user's social behavior and psychological characteristics. The effectiveness of the model is verified by its implementation on the Tencent microblog dataset. The experimental results indicate that the model can better describe the trend of information diffusion in social networks. Highlights • An information model based on multidimensional space and social games is proposed. • Variation of the topic heat lead to changes in user willingness to participate. • The Maximum infection peak is mainly affected by the infection rate and recovery rate. • Variation of dimensions lead to changes in dissemination trend. [ABSTRACT FROM AUTHOR]

Abstract Evolutionary potential games represent a set of biological and ecological models equivalent to multiparticle physical systems for a suitable dynamical rule. In these systems the pair interaction is described by a payoff matrix of two-player games possessing a wider class of interactions. Potential games satisfy criteria related to the Kirchhoff laws and have pure Nash equilibria. Using the bi-matrix formalism of game theory we show a simple method for checking the existence of potential which is related to the absence of cyclic components. It will be shown that potential exists if the game is orthogonal to a suitable set of cycling elementary games resembling voluntary matching pennies games. Relationships among these cyclic components and consequences of player's equivalence are also discussed. Highlights • Relationships between potential games and graphs are developed. • The existence of potential is related to orthogonality criteria between the game and a subset of voluntary matching pennies games. • It is shown that each voluntary rock–paper–scissors game can be built up from two suitable voluntary matching pennies games. [ABSTRACT FROM AUTHOR]

Abstract Cooperation is omnipresent in the evolution of social species. In human societies, people voluntarily associate and cooperate with each other to exchange payments, which results in the inclusion of transaction costs during the process. This paper applies transaction costs to the spatial prisoner's dilemma game to better understand the evolution of cooperation by introducing an active–passive mechanism. In particular, a player who actively proposes the game should pay a transaction costs, while the passive responder pays nothing. Using Monte Carlo simulations and pair-approximation analysis, we investigate the frequency of cooperators in the stationary state for different values of the transaction cost, which maintain the same trend. It is found that there exists an optimal value of the transaction cost at which cooperation is optimally promoted. For small or large values of the transaction cost, the promotive effect decreases, and the evolution of cooperation may be impaired if compared to the absence of the active–passive mechanism. Finally, we explain the emergence of large clusters and theoretically confirm the existence of the optimal transaction cost. The mechanism of transaction costs enhancing cooperation resembles a resonance-like phenomenon, which may be helpful in understanding the cooperative behavior induced by the different behaviors between individuals in society. Highlights • Resonance-like cooperation due to transaction costs in the prisoner's dilemma game. • Improved network reciprocity in the prisoner's dilemma game. • Optimal heterogeneity for the evolution of cooperation in social dilemmas. • Monte Carlo simulations and the pair-approximation analysis confirm the results. [ABSTRACT FROM AUTHOR]

Abstract This paper investigates the stability in a new model of imitation dynamics with discrete distributed delays. Some sufficient conditions of the asymptotical stability for the interior Nash equilibrium of the imitation dynamics with multiple-delay are obtained. Finally, numerical experiments are displayed which support the theoretical results through the Snowdrift game. Highlights • Investigating the stability of the imitation dynamics with discrete distributed delays. • Deriving the sufficient conditions for the imitation dynamics with two delays and multi-delay. • Illustrating the effectiveness of the results through Snowdrift game. [ABSTRACT FROM AUTHOR]

Abstract The emergence and abundance of cooperation in the population of selfish individuals is a challenging problem in evolutionary dynamics. Here we propose two asymmetric information systems in which individuals adopt two different rules to update their strategies. One of the stochastic evolutionary models is mixed by aspiration-driven rule and local information-driven rule, while the other model is mixed by local rule and imitation-driven rule. The proposed heterogeneous systems promote at least one kind of individuals' cooperation. Compared with the standard imitation dynamics and local dynamics, there is always a non-zero probability to support the formation of cooperation in the system with the aspiration and other rules. Furthermore, the more aspiration-driven individuals lead to higher fraction of local-driven cooperators. In the other case, the invasion of individuals who use local information is conductive to promoting the imitation-driven ones' cooperation. In both heterogeneous systems, we find that the individuals who use less information are more likely to cooperate than the ones who use higher information. Highlights • The asymmetric information systems where individuals adopt two different rules to update are proposed. • The heterogeneous systems promote individuals' cooperation. • The individuals who use less information are more likely to cooperate. [ABSTRACT FROM AUTHOR]

It is normal for enterprises to engage in remanufacturing nowadays. Nevertheless, the concern of enterprises and researchers is whether remanufacturers should compete for leadership in supply chains. Considering the WTP for new and remanufactured products differs, this article the evolutionary game theory model in three structures of leadership in supply chains. It investigates the processes of market evolution and choices of strategies when manufacturers and retailers compete or do not compete for leadership in the market. It has been shown in the case of market evolution, according to the 12 conditions formed from different prices that manufacturer and retailer have to pay for competing for leadership, there are five types of ultimate evolutionary stability about the choices of strategies. Further analyses show that these five different evolutionary stability results include nine different evolutionary paths. Analyses of examples further show the evolutionary processes and results in distinct circumstances. This article extends the application of the evolutionary game in remanufacturing supply chains in theory and provides some guidance for enterprises to make decisions when they consider whether they compete for leaders in remanufacturing supply chains in reality. [ABSTRACT FROM AUTHOR]

Highlights • We build a new analytic framework for a vaccination game combined with the susceptible-infected-recovered (SIR) model. • The proposed model can evaluate imperfect provisions such as vaccination giving only partial immunity and intermediate defense measure giving only partial defense against epidemic spreading. • Our model proposes a new strategy i.e., taking both vaccination and intermediate defense measure as an alternative provision alongside taking them separately. • We obtain a phase diagram with which to compare the quantitative effects of the efficiency of an intermediate defense measure with the effectiveness of vaccination. Abstract We build a new analytic scheme that competently reproduces the decision-making process of choosing an imperfect provision based on the evolutionary game theory dovetailed with the SIR model for epidemic spreading dynamics. Aside from considering the two extreme options whether or not taking vaccination, we consider an 'intermediate defense measure' (IDM) that emulates hand-washing, masking, gargling, and taking energy drinks, defined as the third strategy while taking vaccination as well as IDM at the same time as the fourth strategy. In the present study, each of the proposed three imperfect provisions is able to oppress infectious diseases like Flu, Influenza, Ebola, and SARS during an epidemic season with certain extent. Considering an infinite and well-mixed population, a new analytic framework is built to take care of those three cases instead of perfect vaccination. Unlike MAS (multi-agent simulation) approach we conduct our study throughout using the so-called theoretical approach. Besides that, three different strategy updating rules based on evolutionary game theory have also been considered in our proposed model. We successfully obtain phase diagrams showing the final epidemic size, social average payoff and the respective fractions of the different strategy holders using various values of effectiveness and efficiency coefficients. Finally, a comprehensive discussion is made with comparison among the two-, three- and four- strategy models to get a holistic idea justifying how imperfect provisions work during an epidemic spreading. [ABSTRACT FROM AUTHOR]

Evolutionary game dynamics in structured populations has been extensively explored in past decades. However, most previous studies assume that payoffs of individuals are fully determined by the strategic behaviors of interacting parties, and social ties between them only serve as the indicator of the existence of interactions. This assumption neglects important information carried by inter-personal social ties such as genetic similarity, geographic proximity, and social closeness, which may crucially affect the outcome of interactions. To model these situations, we present a framework of evolutionary multiplayer games on graphs with edge diversity, where different types of edges describe diverse social ties. Strategic behaviors together with social ties determine the resulting payoffs of interactants. Under weak selection, we provide a general formula to predict the success of one behavior over the other. We apply this formula to various examples which cannot be dealt with using previous models, including the division of labor and relationship- or edge-dependent games. We find that labor division can promote collective cooperation markedly. The evolutionary process based on relationship-dependent games can be approximated by interactions under a transformed and unified game. Our work stresses the importance of social ties and provides effective methods to reduce the calculating complexity in analyzing the evolution of realistic systems. [ABSTRACT FROM AUTHOR]

Abstract Memory normally plays an important role when people make a decision. Thus, it is reasonable and necessary to introduce the influence of memory in the evolutionary game theory. However, the previous work mainly focuses on prisoner's dilemma, snowdrift game or public good game, but little on stag hunt game. In this paper, a memory-based stag hunt game is proposed. For each iteration, the players in the regular lattices will first choose its neighbor who has the largest accumulated payoff in the last M runs. Then, according to the Femi rule, the player will determine whether learning from the neighbor or not. It is found that the memory length M will promote the cooperation level. The larger the memory length is, the higher the cooperation level will be. Furthermore, when the payoff parameter is less than 0.75, cooperation will always spread the whole regular lattices. As the parameter is larger than 0.75, no matter how large the memory length is, the behavior of defection will always exist. Our work may shed some new light on the study of evolutionary games with memory effect. Highlights • A memory-based stag hunt game is proposed. • It is found that the memory length M will promote the cooperation level. • When the payoff parameter is less than 0.75, cooperation will always spread the whole regular lattices. • As the parameter is larger than 0.75, no matter how large the memory length is, the behavior of defection will always exist. [ABSTRACT FROM AUTHOR]

Abstract The existence of reputation can significantly promote the level of cooperation within the human population. In the recent years, most of the researches were based on binary image score or first-order evaluation standard. In this paper, we propose a second-order reputation evaluation model, in which the individual's image score will change not only in accordance with his own strategy, but also the reputation value of neighbors. Individuals try to enhance their reputation to cooperate with the surrounding high-reputation individuals, and then becomes an influential individual in the population. The existence of this mechanism renders the individuals who at the edge of the clusters formed by the cooperators to rapidly accumulate their reputation values through the adoption of cooperative strategy, and then the cooperative strategy can be spread widely and rapidly in the whole population. Through extensive numerical simulations, it is clearly indicated that the population cooperation behavior will be obviously improved when the individual's influence factor becomes smaller or the reputation step length increases. The current results are further conducive to understanding the emergence of cooperation in many real world systems. Highlights • We propose a public goods game model with second-order reputation evaluation on spatial lattices. • The update of individual's reputation needs to consider individual's own strategy and his opponent's reputation. • The simulation result indicates that the cooperation frequency will be increased when use a larger reputation step length p. • The second-order reputation evaluation model can effectively increase the cooperation frequency in the spatial PGG. [ABSTRACT FROM AUTHOR]

Highlights • A dynamic model of the Wright-Fisher process by introducing different selection intensities for different strategies is established. • Under weak selection, we obtained the analytical expressions of fixation probability which is not only related to a game matrix but also to different selection intensities. • We compared our results with those of a Moran dynamic process with different intensities. For two processes, the conditions conducive to the strategy's taking fixation are the same. Abstract Evolutionary game dynamics in finite populations can be described by a frequency-dependent, stochastic Wright-Fisher process. The fitness of individuals in a population is not only linked to environmental conditions but also tightly coupled to the types and frequencies of competitors, leading to different types of individuals with different selection intensities. We studied a 2 × 2 symmetric game in a finite population and established a dynamic model of the Wright-Fisher process by introducing different selection intensities for different strategies. Thus, we provided another effective way to study the evolutionary dynamics of a finite population and obtained the analytical expressions of fixation probabilities under weak selection. The fixation probability of a strategy is not only related to a game matrix but also to different selection intensities. The conditions required for natural selection to favor one strategy and for that strategy to be an evolutionary stable strategy (ESS N) are specified in our model. We compared our results with those of a Moran dynamic process with different selection intensities to explore these two processes better. In the two processes, the conditions conducive to the strategy's taking fixation are the same. By simulation analysis, the dynamic relationships between the fixation probabilities and selection intensities were intuitively observed in the prisoner's dilemma, coordination, and coexistence games. The fixation probability of the cooperative strategy in the prisoner's dilemma decreases with the increase of its own selection intensity. In the coexistence and coordination games, the fixation probability of the cooperative strategy increases with its own selection intensity. For the three types of games, the fixation probability of the cooperative strategy decreases with the increase of the selection intensity of the defection strategy. [ABSTRACT FROM AUTHOR]

Abstract Evolutionary game theory (EGT) provides a powerful tool with which to unpack the interactive strategies of polluting enterprises (PEs), local government regulators (LG), and central government planners (CG) in China. Here, the prevailing institutional system of fiscal decentralization sees regulatory mandates set by the CG and enforced at the LG level. This delegation shapes managers' incentives when deciding the degree to which firms will incur costs to reduce pollution and comply with state directives. Manager's choice sets draw shape from decisions at the LG level, where regulators balance the pursuit of environmental quality with the economic payoffs of tacit collusion with industry. LG and PEs incentives reciprocally shape and draw shape from outcomes at the CG level, where policymakers decide the degree to which they will support and supervise the behavior of LGs. By exploring the evolution of different participants' behavior and their evolutionary stable strategy (ESS) in line with the duplication of dynamic equations, EGT enables a robust, quantitative analysis of this iterative, interactive, three-player game. A numerical example serves to verify the theoretical results and support four key insights. First, the selection of environmental strategies manifest in a dynamic process of constant adjustment and optimization. Second, LGs outperform by integrating decisions from both CG and PEs in weighing alternative environmental strategies. Third, reducing regulatory costs at the CG level cascades to strengthen penalties for local violations and improve mitigation incentives in ways that aid an evolutionary game to converge on an ideal decision state. Fourth, a stable equilibrium cannot persist to allow LGs to sustain behaviors towards a "race to the bottom", even in the total absence of central regulation or high levels of dominance of polluting firms of LG regulators. EGT thus not only outcomes shed light on the full variation set of game outcomes, it also reveals the consequences of variable levels of collusion between LGs and PEs and options for the redesign of incentive mechanisms to reform the regulatory regime and improve market outcomes in China. Highlights • Tripartite evolutional game reveals strategic adjustments of environmental regulation under Chinese fiscal decentralization. • Central enforcement and firm-level mitigation proves dynamic to local government implementation. • Case-based observations inform the deduction of parameter thresholds for convergence to an equilibrium ideal state. [ABSTRACT FROM AUTHOR]

Abstract In peer-to-peer service networks, autonomous agents gain utilities through getting services from others. However, providing services is so costly that rational agents may prefer to defect rather than to cooperate. In order to provide scalable and robust services in such networks, incentive mechanisms need to be introduced. In this paper, we propose a novel approach RIM (Recommendation Incentive Mechanism) by building a cooperative agents recommendation system. And, in order to investigate the acceptance and performance of the proposed RIM, evolutionary game theory has been used. By studying the evolutionary stable state, we demonstrate the performance of the RIM-based model by both considering two scenarios PRIM/IRIM (Perfect/Imperfect Recommendation Incentive Mechanism). To comprehensively confirm the robustness of our mechanism: (1) OCMP (One Consumer Multi-service Providers) method has been discussed, in which agent could simultaneously request services from k (k > 1) different agents; (2) a FS (Four-Strategies) game model has been further introduced; (3) QS (Quantity Sensitivity) scenario has been researched, in which the utility of an agent is sensitive to the amount of received services. By using the Lyapunov stability theory, it is qualitatively proved that non-cooperative agents can be well suppressed in our proposed RIM. Finally, extensive numerical and simulation experiments are conducted to highlight the performance and validate the theoretical properties of our model. [ABSTRACT FROM AUTHOR]

Abstract In realistic world, the role or influence of each individual is heterogeneous and usually varies according to surroundings. Inspired by this fact, here we study the emergence of cooperative behavior in weighted networks under the coevolution of game strategy and node weight, where the node weight is used to mimic the role or influence of subjects. In the prisoner's dilemma, if an individual's fitness exceeds the aspiration level, its weight becomes larger; otherwise weight decreases. While such an adjustment of weight is defined by the intensity parameter δ, it is interesting that there is an optimal range for δ guaranteeing the best evolution of cooperation. The facilitation of cooperative behavior mainly depends on the weight distribution of players, which is based on the formation of a cooperative cluster controlled by high-weight cooperators. These cooperators are able to prevail against defectors even when there is a large temptation to defect. Our research provides a viable route to resolve social dilemma and will inspire further applications. [ABSTRACT FROM AUTHOR]

Nonlocal Lotka-Volterra models have the property that solutions concentrate as Dirac masses in the limit of small diffusion. Motivated by the existence of moving Dirac-concentrations in the time-dependent problem, we study the qualitative properties of steady states in the limit of small diffusion. Under different conditions on the growth rate and interaction kernel as motivated by the framework of adaptive dynamics, we will show that as the diffusion rate tends to zero the steady state concentrates (ⅰ) at a single location; (ⅱ) at two locations simultaneously; or (ⅲ) at one of two alternative locations. The third result in particular shows that solutions need not be unique. This marks an important difference of the non-local equation with its local counterpart. [ABSTRACT FROM AUTHOR]

Abstract Strategy preference is a nonnegligible factor in the evolution of cooperation. In the present paper, we propose a modified strategy updating model, in which strategy preference has a significant influence on the strategy adoption. Strategy preference adjusts the probability of imitation according to partner's strategy in the spatial prisoner's dilemma game. This characteristic depicts the subjectively cognitive ability of players in decision making. To explore the effect of the newly introduced mechanism, we also control the proportion of players using this new model. Numerical results chiefly focus on the evolution and proportion of cooperation, which are obtained under different proportions of this mechanism and intensities of strategy preference. For this dynamics, the results show that the fraction of cooperators presents a growth trend within a wide range of parameters. To validate the generality of this mechanism, we also employ the snowdrift game. Moreover, the evolution of cooperation on Erdős–Rényi random graphs is studied for the prisoner's dilemma game. Interestingly, our analysis also reveals that the one's strategy preference can influence the strategy selection of others. The results are conducive to understanding the emergence and persistence of cooperation during the strategy adoption in reality. Highlights • A new strategy updating rule based on strategy preference is proposed. • Strategy preference can improve the individual readiness for cooperation. • The fraction of cooperators is enhanced effectively compared with the classical case. [ABSTRACT FROM AUTHOR]

The ride-hailing industry is a new business form that combines traditional taxi services with Internet technology and a sharing economy. However, after its emergence, countries have focused on finding ways to regulate this industry. The regulation of ride-hailing has gone through three stages: from denial of negation to laissez-faire and prudential supervision. This study focuses on the market regulation of the ride-hailing industry, discusses whether ride-hailing platforms require strict regulation under the current Internet setting, and provides evidence for this problem from the perspective of evolutionary game theory between the behavior of the government and the platforms. This study argues that both ride-hailing platforms and the government are evolutionary game players with bounded rationality, constantly adjusting their strategies through confrontation, dependence, and restriction. Therefore, this study constructs a two-dimensional game model between the government and ride-hailing platforms and analyzes the stability strategies of the two participants in different scenarios, to clarify the game behavior and the game return matrix. Assuming that loose government regulation and the standard operation of the ride-hailing platforms are the optimal Pareto equilibrium of the game system, the study concludes that this optimal equilibrium cannot be achieved under the current conditions. Through parameter analysis and sample simulation calculations, the system can be directed toward this equilibrium by reducing government supervision cost and increasing government punishment. This provides a theoretical basis for the government to regulate the ride-hailing industry from the perspective of quantitative analysis. Related implications are finally proposed, which can help the decision-makers better understand the regulation countermeasures of the government and ride-hailing platforms. [ABSTRACT FROM AUTHOR]

Quantised consensus has been used in the context of opinion dynamics. In this context agents interact with their neighbours and they change their opinion according to their interests and the opinions of their neighbours. We consider various quantised consensus models, where agents have different levels of susceptibility to the inputs received from their neighbours. The provided models share similarities with collective decision making models inspired by honeybees and evolutionary games. As first contribution, we develop an evolutionary game-theoretic model that accommodates the different consensus dynamics in a unified framework. As second contribution, we study equilibrium points and extend such study to the symmetric case where the transition probabilities of the evolutionary game dynamics are symmetric. Symmetry is associated with the case of equally favourable options. As third contribution, we study stability of the equilibrium points for the different cases. We corroborate the theoretical results with some simulations to study the outcomes of the various models. [ABSTRACT FROM AUTHOR]

Abstract Strategy updating is generally based on payoff comparison and strategy learning within the interaction pairs on networks in evolutionary games. In many previous works, the interaction and learning environments are assumed to be the same networks. However, in the real world, they might be different. In this work, we consider the spatial public goods game on two-layer networks, where the interaction and learning environments are represented by two asymmetric layers, respectively. We focus on the effects of edge overlap ω between the interaction and learning networks on the evolution of cooperation. The simulation results show that, the effects of ω on the evolution of cooperation depend on the synergy factor r. For relatively small r , higher overlap between the interaction and learning environments will be more favorable for cooperation. However, the situation is reverse for relatively large r , where the lower overlap between the interaction and learning environments results in higher level of cooperation. We also find that the asymmetry between the interaction and learning environments inhibits the coexistence of the cooperators and defectors. Furthermore, we show that the results of the model are robust to the underlying networks with different node degrees. [ABSTRACT FROM AUTHOR]

Highlights • Game theory is used to explain why China choose strategy of cooperation rather than competition in international affairs. • Cooperation strategy on development assistance to Africa is more likely a rational choice for both China and Japan. • This analytical framework can be applied to other international affairs involving China and other countries. Abstract Still influenced by the cold war thinking, many countries – especially looking to new rising powers – might interact in the international scenario through competition, instead than cooperation. However, China has seen more opportunities in cooperation than challenges in competition. Since 2013, Chinese president Xi Jinping pointed out clearly in various public occasions that this world has become a community of common destiny. In this paper, we used an asymmetric dynamic evolution game model, adding the hypothesis of win-win game, to analyze why China would like to choose the strategy of cooperation, rather than competition, in international affairs. We applied this analytical framework to the case study of Chinese and Japanese environmental assistance programs to Africa. We found that, based on the traditional game theory, under the hypothesis of the cold war mentality, China and Japan may act as mutual rivals. Under this circumstance, China, as an emerging developing country, will more likely choose the strategy of competition, rather than cooperating with other countries. Instead, Japan, as a traditional developed country, will more likely choose to cooperate, rather than competing with China, especially if the expected cost of the failure of the competition is high. However, in the new hypothesis of win-win game analysis, we found that cooperation strategy on development assistance to Africa is more likely a rational choice for both China and Japan. Thus, we suggest that China might keep practicing its win-win strategy and do not use the outdated zero-sum game and winner-take-all strategy as some of its counterparts may probably do. This analytical framework can be applied to other international affairs involving China and other countries. [ABSTRACT FROM AUTHOR]

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

We consider the influence of the number of manufacturing partners on the game of production technologies, which takes place between two manufacturers with different production technologies in a two-echelon manufacturing supply chain network. Firstly, this study analyzes the influence of the number of manufacturing partners on the bilateral production cooperative relation between upstream and downstream manufacturers, finding that the number of manufacturing partners significantly influences bilateral cost-sharing proportion caused by "eliminating production technology differences between them." Furthermore, we explore corresponding conditions for reaching different evolutionary stable strategy of the two parties in the game of production technology, concluding that manufacturers would not have better performance and either they have more and more or fewer and fewer manufacturing partners. Instead, there exists a critical interval in the number of manufacturing partners in which manufacturers regularly choose certain evolutionary stable strategies all the time. Finally, according to the example analysis on evolutionary stable states in the game and the sensitivity analysis on relevant parameters that affect the game relationship, it is shown that whether the "collaborate" strategy would eventually be chosen by the manufacturer was correlated negatively with its cost coefficient for eliminating production technology differences, but positively with the other party's cost coefficient and extra profit in bilateral cooperation. [ABSTRACT FROM AUTHOR]

The escalation of complexity is a commonly cited benefit of coevolutionary systems, but computational simulations generally fail to demonstrate this capacity to a satisfactory degree. We draw on a macroevolutionary theory of escalation to develop a set of criteria for coevolutionary systems to exhibit escalation of strategic complexity. By expanding on a previously developed model of the evolution of memory length for cooperative strategies by Kristian Lindgren, we resolve previously observed limitations on the escalation of memory length by extending operators of evolutionary variation. We present long-term coevolutionary simulations showing that larger population sizes tend to support greater escalation of complexity than smaller ones do. Additionally, we investigate the sensitivity of escalation during transitions of complexity. The Lindgren model has often been used to argue that the escalation of competitive coevolution has intrinsic limitations. Our simulations show that coevolutionary arms races can continue to escalate in computational simulations given sufficient population sizes. [ABSTRACT FROM AUTHOR]

Highlights • When the penalty strategy is static payment, the strategy selections fluctuate repeatedly. • Increasing penalties can quickly control the occurrence of illegal behaviours in the short term. • Increasing penalties can increase the fluctuation of illegal behaviours in the long term. • The dynamic penalty strategy can effectively restrain the fluctuations and stabilize the game. • The stable state and equilibrium values are not affected by the initial value changes. Abstract Coal-mine safety regulation is an important approach to ensure safe production in the mining industry. The existing literature on China's coal-mine safety regulation focuses mainly on statically analysing the game between two stakeholders and neglects the dynamic process of game playing under bounded rationality. Moreover, when there are a number of coal-mining enterprises, there are different interest demands between them in the context of regulation. Therefore, this paper explores the use of evolutionary game theory to describe the long-term dynamic process of multi-player game playing in coal-mine safety regulation under the condition of bounded rationality. Furthermore, the multi-player evolutionary game is simulated by adopting system dynamics to analyse the implementation effect of different penalty strategies on the game process and game equilibrium. The simulation results are as follows. First, when the penalty strategy is static payment, the strategy selections of the stakeholders fluctuate repeatedly. Moreover, increasing the penalties can quickly control the occurrence of coal-mine enterprises' illegal behaviours in the short term, but in the long term, it can increase the fluctuation of coal-mine enterprises' illegal behaviours and make the game process more difficult to control. Second, when the penalty strategy is dynamic payment, the dynamic penalty strategy can effectively restrain the fluctuations existing in the game play and stabilize the game, reducing the safety risks caused by uncertainty. Moreover, the stable state and equilibrium values are not affected by the initial value changes. The application of system dynamics when simulating the multi-player game process is an effective way to analyse the implementation effects of different penalty strategies, which provides a more effective solution to the study of complex multi-player game problems. [ABSTRACT FROM AUTHOR]

Abstract The data warehouse contains a number of views that are used to respond to the system queries. On the one hand, the time consuming process of responding to analytical queries of the data warehouse requires to store intermediate views for efficient query answering, and on the other hand, large numbers and high volumes of intermediate views, make the storage of all views impossible. Hence, choosing the optimal set of views for materialization is one of the most important decisions in the data warehouses design, in order to increase efficiency of query answering. Since the search space of the problem is very large, searching among the collections of all possible views of a data warehouse is very expensive and thus, it is necessary to use methods to solve the problem in an acceptable time. Random methods, such as game theory-based optimization approaches, try to increase the speed of selecting materialized views by finding near optimal solutions. In this article, an evolutionary game theory-based method to materialized view selection in the data warehouse is represented which exploits the multiple view processing plan structure to represent the search space of the problem. In this method, a population of players is created, each of which is a solution to the problem. Three strategies are considered for each player and at each repetition of the game, players attempt to choose the best strategy for themselves. At the end of the game, the final solution is calculated according to the strategies selected by the players. Our empirical evaluations revealed that the proposed method has appropriate convergence for large data warehouses and its execution time is very good. It is also shown that the quality of the solutions of the proposed method is more appropriate than other similar random methods. [ABSTRACT FROM AUTHOR]

We identify a novel 'cultural red king effect' that, in many cases, results in stable arrangements which are to the detriment of minority groups. In particular, we show inequalities disadvantaging minority groups can naturally arise under an adaptive process when minority and majority members must routinely determine how to divide resources amongst themselves. We contend that these results show how inequalities disadvantaging minorities can likely arise by dint of their relative size and need not be a result of either explicit nor implicit prejudices, nor due to intrinsic differences between minority and majority members. [ABSTRACT FROM AUTHOR]

How robust is the welfare state when confronting open borders? To answer that question, we develop an evolutionary game-theoretic model combined with an ingroup-outgroup model. The simulations reveal that welfare states in general will transform into low-welfare societies unless the societies in time generate a sufficiently large amount of social recognition of the reciprocators in such a crisis. The recognition implies that the "always cooperators" in favour of supportive policies towards free riders need to step down and hand over privileges to those willing to reciprocate, namely the "willing punishers". The open-border society is modelled by letting a small amount of random types enter the society each year. Interestingly, it is not the defectors who compromise high-welfare societies. Instead, it is the excessive presence of cooperators who crowd out the reciprocators, thus making society increasingly vulnerable to free riding. This accentuates the need for timely recognition and actions against the risk of moving towards a low-welfare society. [ABSTRACT FROM AUTHOR]

Extortion strategies can unilaterally transcend any opponent's expected payoffs and promote cooperative behaviors in an iterated prisoner's dilemma game. However, extortion strategies have the evolutionary instability if the players game with uniform structure. In this paper, we study the influence of extortion on the evolution of cooperation in the scale-free network with the player's game payoffs calculated by average payoffs and the strategy update rule according to the replicator dynamics rule. Firstly, we study the stability of evolutionary game results after introducing the extortion strategy and the influence of evolution extortion on cooperation. In addition, we compare the results of our model with the donation games of the accumulated payoff in the BA networks. Moreover, we study the influence of the model parameters on game results. The results show that extortion can form long-term stable relationships with neighbors and the average payoffs' inhibiting effect of cooperative behaviors disappear after introducing the extortion strategies in the scale-free network. The smaller value of the extortion actor and the benefit factor have a greater effect on the stability density of the strategies but the initial strategy density does not. [ABSTRACT FROM AUTHOR]

Abstract In population genetics, fixation of traits in a demographically changing population under frequency-independent selection has been extensively analysed. In evolutionary game theory, models of fixation have typically focused on fixed population sizes and frequency-dependent selection. A combination of demographic fluctuations with frequency-dependent interactions such as Lotka–Volterra dynamics has received comparatively little attention. We consider a stochastic, competitive Lotka–Volterra model with higher order interactions between two traits. The emerging individual-based model allows for stochastic fluctuations in the frequencies of the two traits and the total population size. We calculate the fixation probability of a trait under differing competition coefficients. This fixation probability resembles, qualitatively, the deterministic evolutionary dynamics. Furthermore, we partially disentangle the selection effects into their ecological and evolutionary components. We find that changing the evolutionary selection strength also changes the population dynamics and vice versa. Thus, a clean separation of the ecological and evolutionary effects is not possible. Instead, our results imply a nested interaction of the evolutionary and ecological effects. The entangled eco-evolutionary processes thus cannot be ignored when determining fixation properties in a co-evolutionary system. [ABSTRACT FROM AUTHOR]