Focal Player Research Articles

Do people imitate when making decisions? Evidence from a spatial Prisoner's Dilemma experiment.

How do people decide which action to take? This question is best answered using Game Theory, which has proposed a series of decision-making mechanisms that people potentially use. In network simulations, wherein games are repeated and pay-off differences can be observed, those mechanisms often rely on imitation of successful behaviour. Surprisingly, little to no evidence has been provided about whether people actually imitate more successful opponents when altering their actions in that context. By comparing two experimental treatments wherein participants play the iterated Prisoner’s Dilemma game in a lattice, we aim to answer whether more successful actions are imitated. While in the first treatment, participants have the possibility to use pay-off differences in making their decision, the second treatment hinders such imitation as no information about the gains is provided. If imitation of the more successful plays a role then there should be a difference in how players switch from cooperation to defection between both treatments. Although, cooperation and pay-off levels do not appear to be significantly different between both treatments, detailed analysis shows that there are behavioural differences: when confronted with a more successful co-player, the focal player will imitate her behaviour as the switching is related to the experienced pay-off inequality.

The Dynamic Approaches in Enhancing Citizenry Participation in South African Local Government

The Constitution of South Africa is underpinned by the standards of good administration, featuring the significance of open interest as a basic component of an effective local administration, with respect to subject inclusion in a "local government" organization. The interest of citizens to participate in local government issues is viewed as having a noteworthy ramification on democratizing administration conveyance beyond simply delegate government, by having people and community as focal role players all the while. In South Africa, the need for the community to participate in local government administration offers a more prominent control of the underprivileged over their own circumstance and guarantees their full inclusion in deciding their very own formative needs. Along these lines, districts must assume a noteworthy job in advancing the majority rules system of democracy and guaranteeing that the community takes an interest in choices that influence them specifically. This study contends that regardless of its perplexing structures, obstructions, and serious administrative difficulties, citizens’ interest stay vital to the accomplishment of local government administration conveyance. The idea of community support as an indispensable factor for a fruitful government and delivery of good administration in the local circle was examined in this paper. The possibility of community interest in South Africa was bolstered by the declaration of different administrative structures which supported the contribution of individuals in local administration and strategy making. For instance, the White Paper on Local Government (1998) a qualitative analysis method was adopted by this study and the rational model was applied to place things in the correct points of view.

Role of vaccine efficacy in the vaccination behavior under myopic update rule on complex networks.

How to effectively prevent the diffusion of infectious disease has become an intriguing topic in the field of public hygienics. To be noted that, for the non-periodic infectious diseases, many people hope to obtain the vaccine of epidemics in time to be inoculated, rather than at the end of the epidemic. However, the vaccine may fail as a result of invalid storage, transportation and usage, and then vaccinated individuals may become re-susceptible and be infected again during the outbreak. To this end, we build a new framework that considers the imperfect vaccination during the one cycle of infectious disease within the spatially structured and heterogeneous population. Meanwhile, we propose a new vaccination update rule: myopic update rule, which is only based on one focal player's own perception regarding the disease outbreak, and one susceptible individual makes a decision to adopt the vaccine just by comparing the perceived payoffs vaccination with the perceived ones of being infected. Extensive Monte-Carlo simulations are performed to demonstrate the imperfect vaccination behavior under the myopic update rule in the spatially structured and heterogeneous population. The results indicate that healthy individuals are often willing to inoculate the vaccine under the myopic update rule, which can stop the infectious disease from being spread, in particular, it is found that the vaccine efficacy influences the fraction of vaccinated individuals much more than the relative cost of vaccination on the regular lattice, Meanwhile, vaccine efficacy is more sensitive on the heterogeneous scale-free network. Current results are helpful to further analyze and model the choice of vaccination strategy during the disease outbreaks.

Evolution of cooperation in the spatial public goods game with the third-order reputation evaluation

In this letter, in order to deeply explore the role of individual reputation in the evolutionary game dynamics, we present a new third-order reputation evaluation model to discuss the evolution of cooperation in the spatial public goods game. In the current model, we should not only consider the strategy (cooperation, C or defection, D) of a focal player, but also take his own reputation and his opponent's reputation status into account. Among them, the individual reputation will be divided into being good and bad according to the specified threshold, and the good player will be endowed with the more influential strategy transfer ability, which further helps to create the clusters of cooperative and good players within the population and then fosters the cooperation. A large plethora of experimental simulation results indicate that four rules under the third-order reputation mechanism can lead to the promotion of cooperation when compared to the traditional public goods game model. The current work is conductive to a better understanding of the persistence and emergence of collective cooperation in real-world systems.

Reputation-based adaptive adjustment of link weight among individuals promotes the cooperation in spatial social dilemmas

The relationships among individuals on the network are often dynamic and adaptive adjustment with the interactions, which have a strong effect on the cooperation behavior. In this paper, we propose a new spatial evolutionary game model to further investigate the emergence and persistence of cooperation, in which the link weights among individuals are dynamically and adaptively adjusted by comparing between their own reputation and the average one of their nearest neighbors. If the reputation of the focal player is greater than the average one of his/her nearest neighbors, the nearest neighbors around the focal player will follow him/her, thus the link weight between the nearest neighbors and the focal player will increase by one unit as a reward. In contrast, the corresponding link weight will be decreased by one unit as a punishment. In addition, we use another parameter ε to control the possible range of link weight. By conducting extensive Monte Carlo numerical simulations in the prisoner’s dilemma and the snowdrift games, it is clearly verified that the adaptive adjustment of link weight can dramatically promote the evolution of cooperation, and the cooperation can be further elevated into a higher level when compared with the standard spatial dilemma game. The current results are helpful for us to better understand the influence of dynamic link weight on the collective cooperation behavior.

Competition and partnership between conformity and payoff-based imitations in social dilemmas

Learning from a partner who collects a higher payoff is a frequently used working hypothesis in evolutionary game theory. One of the alternative dynamical rules is when the focal player prefers to follow the strategy choice of the majority in the local neighborhood, which is often called a conformity-driven strategy update. In this work we assume that both strategy learning methods are present and compete for space within the framework of a coevolutionary model. Our results reveal that the presence of a payoff-driven strategy learning method becomes exclusive for high sucker’s payoff and/or high temptation values that represent a snowdrift game dilemma situation. In general, however, the competition of the mentioned strategy learning methods could be useful to enlarge the parameter space where only cooperators prevail. The success of cooperation is based on the enforced coordination of cooperator players which reveals the benefit of the latter strategy. Interestingly, the payoff-based and the conformity-based cooperator players can form an effective alliance against defectors that can also extend the parameter space of full cooperator solution in the stag-hunt game region. Our work highlights that the coevolution of strategies and individual features such as the learning method can provide a novel type of pattern formation mechanism that cannot be observed in a static model, and hence remains hidden in traditional models.

Do Long-time Team-mates Lead to Better Team Performance? A Social Network Analysis of Data from Major League Baseball

To estimate the effects of team-mate shared experience on overall team performance as well as to determine whether concentration of time together among subgroups of players and/or focal players enhances team performance. Social network analysis (SNA) was used to model 30 active Major League Baseball teams from 2006 to 2015 with years of experience together connecting players resulting in 300 individual team networks. Social network metrics of network density, network centralization, and average weighted degree were computed and analyzed with team attributes by generalized least squares regression to predict wins, and team rank. Logistic regression was used to predict binary outcomes of world series and division wins. Network density was negatively associated with team rank (β = - 0.115, p = .05), while average weighted degree was positively associated with team rank (β = 0.147, p = .01). On average, each extra year of shared player time per team was associated with 14.86% higher probability of winning a division title (B = 2.69, exp(B) = 14.86, p = .05). Each extra shared year of infield membership among team-mates predicted 2.4% lower odds of winning the world series (B = -0.024, exp(B) = 0.976, p = .01), and each extra shared year between outfield players predicted 2.9% lower probability of winning a team's division (B = -0.029. exp(B) = 0.972, p = .05). Prolonged shared time between players is beneficial when it is spread evenly among all players of the team, whereas having few focal players who have been on a team together for many years is a disadvantage to overall performance.

Cooperation enhanced by the coevolution of teaching activity in evolutionary prisoner's dilemma games with voluntary participation.

Voluntary participation, as an additional strategy involved in repeated games, has been proved to be an efficient way to promote the evolution of cooperation theoretically and empirically. Besides, current studies show that the coevolution of teaching activity can promote cooperation. Thus, inspired by aforementioned above, we investigate the effect of coevolution of teaching activity on the evolution of cooperation for prisoner’s dilemma game with voluntary participation: when the focal player successfully enforces its strategy on the opponent, his teaching ability will get an increase. Through numerical simulation, we have shown that voluntary participation could effectively promote the fraction of cooperation, which is also affected by the value of increment. Furthermore, we investigate the influence of the increment value on the density of different strategies and find that there exists an optimal increment value that plays an utmost role on the evolutionary dynamics. With regard to this observation, we unveil that an optimal value of increment can lead to strongest heterogeneity in agents’ teaching ability, further promoting the evolution of cooperation.

Donation of richer individual can support cooperation in spatial voluntary prisoner's dilemma game

The compassionate behavior is present throughout the human society, and rich people always could not help having sympathy for poor individual. Inspired by this fact, we consider a donation model to describe the emergency and maintenance of cooperation with voluntary participate in spatial prisoner's dilemma game and we study this model on a square lattice. In detail, when the focal player has the least income in the group which includes his nearest four neighbors and himself, one of his neighbors who has the highest income will donate some proportion of his extra money to him. On the other hand, if focal individual is not the poorest, he will donate some incomes to his poorest neighbor. Through numeric simulation, we conclude that our donation model can promote the evolution of cooperation monotonously. Especially, the larger proportion payoff rich people can contribute, the higher level of cooperation we can get.

Realistic decision-making processes in a vaccination game

Previous studies of vaccination games have nearly always assumed a pairwise comparison between a focal and neighboring player for the strategy updating rule, which comes from numerous compiled studies on spatial versions of 2-player and 2-strategy (2 × 2) games such as the spatial prisoner’s dilemma (SPD). We propose, in this study, new update rules because the human decision-making process of whether to commit to a vaccination is obviously influenced by a “sense of crisis” or “fear” urging him/her toward vaccination, otherwise they will likely be infected. The rule assumes that an agent evaluates whether getting a vaccination or trying to free ride should be attempted based on observations of whether neighboring non-vaccinators were able to successfully free ride during the previous time-step. Compared to the conventional updating rule (standard pairwise comparison assuming a Fermi function), the new rules generally realize higher vaccination coverage and smaller final epidemic sizes. One rule in particular shows very good performance with significantly smaller epidemic sizes despite comparable levels of vaccination coverage. This is because the specific update rule helps vaccinators spread widely in the domain, which effectively hampers the spread of epidemics.

Heterogeneous fitness promotes cooperation in the spatial prisoner's dilemma game

Many literatures suggest that incorporating the environment of a focal player (denoted by the average payoff of its all immediate neighbors) into its fitness can promote cooperation in spatial evolutionary games. However, the immediate neighbors influence the focal one to varying degree. Inspired by these, we quantify the focal player's environment with a weighted average payoff of its all immediate neighbors via two interdependent parameters. Numerous simulations show that two moderate parameter pairs favor cooperation, in addition, when the contribution of all immediate neighbors’ payoffs to the environment is negative, the cooperation is promoted remarkably. The generality of this mechanism is verified on different networks and more games. Our work might shed light on the understanding of the evolution of cooperative behaviors in real life.

A sweeter win: When others help us outperform them

To succeed in today's workplaces, people often need to outperform the persons who helped them succeed. In three studies we assessed how doing so affects well-being, prosocial behavior and social perceptions. In the first two studies participants took part in a competitive version of a virtual ball-toss game, with different financial incentives in each study. Depending on condition participants either obtained the majority of the ball tosses or almost no ball tosses. Importantly, participants either “earned” this outcome as a result of their own performance or were “granted” this outcome as a result of the performance of the other players. Study 3 featured the same conditions and a combination of the incentives. However, participants now observed one of the games and rated the anticipated reaction of a focal player. The results revealed that (1) winning was better than losing, (2) especially when people's win was granted to them and less so when they earned it for themselves, (3) which resulted in higher well-being and prosocial behavior, and also maintained meta-perceptions and other-perceptions of competence and enhanced meta-perceptions and other-perceptions of warmth. These results advance theories on interpersonal competition, social comparison, and in/exclusion.

Logit selection promotes cooperation in voluntary public goods game

In this paper, we present a simple yet effective model to promote cooperation in selfish population, namely, a spatial evolutionary public goods game model that includes three kinds of players: cooperator, defector and loner. In spatial settings, the players locate on a regular lattice, and each player randomly selects one strategy, then all the player acquire their payoffs with their four nearest neighbors, after that the focal player chooses a neighbor based on the logit selection model and updates his/her strategy in accordance with a random sequential simulation procedure. The Monte Carlo simulation results demonstrate that the ruthless invasion of defectors can be efficiently prevented by the loners, especially when enhanced factor r is low. Further interesting is the fact that the introduction of a logit selection model, making the fittest neighbors more likely to act as sources of adopted strategies, effectively promotes the evolution of cooperation even if the loner is absence.

Which facilitates the evolution of cooperation more, retaliation or persistence?

The existence of cooperation in this world is a mysterious phenomenon. One of the mechanisms that explain the evolution of cooperation is repeated interaction. If interactions between the same individuals repeat and individuals cooperate conditionally, cooperation can evolve. A previous study pointed out that if individuals have persistence (i.e., imitate its “own” behavior in the last move), cooperation can evolve. However, retaliation and persistence are not mutually exclusive decisions, but rather a trade-off in the decision making process of individuals. Players can refer to the opponent's behavior and if the actor and the opponent opted for the different alternative in the last move, conditional cooperators have to give up either retaliation or persistence. The previous study also investigated this, and has revealed that the individual should give more importance to retaliation than to persistence. However, this study has assumed that the errors in perception are absent. In this world, errors in perception are present, and trying to imitate the opponent player can sometimes end in failure. And, it might be that imitating the focal player, which definitely ends in success, is more beneficial than trying to imitate the opponent player, which can end in failure especially when the error rate in recognition is large. Here, this paper uses evolutionarily stable strategy (ESS) analysis and analyzes the stability for reactive strategies against the invasion by unconditional defectors in the iterated prisoner's dilemma game. And our analysis reveals that even if we take errors in perception into consideration, retaliation facilitates the evolution of cooperation more than persistence unexpectedly. In addition, we analyze the stability for reactive cooperators against the invasion by a strategy other than unconditional defectors. Moreover, we also analyze the deterministic model in which unconditional cooperators, unconditional defectors, and the reactive strategy at the same time.

Asymmetric evaluation promotes cooperation in network population

The evolution of cooperation remains a fundamental challenge in human society. Many previous studies investigated these questions via spatial reciprocity, where players obtain their payoffs by interacting with their direct neighbors. It has also been verified that environmental factors can influence the evolution of cooperation theoretically and empirically. In reality, however, individuals may have the limit knowledge about their indirect neighbors. Inspired by this fact, we consider an asymmetric fitness calculation mechanism, which only integrates the environment factors into the focal player, to explore the evolution of cooperation. Here, the environmental factor is defined as the average payoff of all individual neighbors, which is regulated by a tunable parameter u. Through numerical simulation, we find that, compared with the traditional version (u=0), that the cooperation level can be greatly enhanced when u is positive. Interestingly, the larger the value of u, the higher the level of cooperation. Finally, to explore the generality of this finding, we have tested the results on different topologies.

Utility Evaluation Based on One-To-N Mapping in the Prisoner's Dilemma Game for Interdependent Networks.

In the field of evolutionary game theory, network reciprocity has become an important means to promote the level of promotion within the population system. Recently, the interdependency provides a novel perspective to understand the widespread cooperation behavior in many real-world systems. In previous works, interdependency is often built from the direct or indirect connections between two networks through the one-to-one mapping mode. However, under many realistic scenarios, players may need much more information from many neighboring agents so as to make a more rational decision. Thus, beyond the one-to-one mapping mode, we investigate the cooperation behavior on two interdependent lattices, in which the utility evaluation of a focal player on one lattice may not only concern himself, but also integrate the payoff information of several corresponding players on the other lattice. Large quantities of simulations indicate that the cooperation can be substantially promoted when compared to the traditionally spatial lattices. The cluster formation and phase transition are also analyzed in order to explore the role of interdependent utility coupling in the collective cooperation. Current results are beneficial to deeply understand various mechanisms to foster the cooperation exhibited inside natural, social and engineering systems.

Inferring the reputation enhances the cooperation in the public goods game on interdependent lattices

In this paper, we mainly probe into the evolution of cooperation in the spatial public goods game on interdependent lattices by introducing the reputation inferring mechanism into the strategy selection. During the strategy update, the individual reputation is commonly determined by two corresponding partners on interdependent lattices, where the imitated neighbors are chosen in accordance with the average, maximum and minimum of reputation values between two partners within the neighborhood of a focal player. A large plethora of simulations indicate that three reputation computing rules all lead to the promotion of cooperation when compared to the traditional public goods game model. Among them, the promotion of cooperation under the average and minimum schemes are relatively better than that produced by the maximum rule. The detailed cluster formation and reputation distribution are provided to illustrate the slight difference between the outcomes under these three decision making criterions, in which the choice of learning objects is governed by their reputations. Thus, we can conclude that current results are further conducive to understanding the universal and persuasive cooperation within many natural, biological, social and even man-made systems.

Variability in group size and the evolution of collective action

Models of the evolution of collective action typically assume that interactions occur in groups of identical size. In contrast, social interactions between animals occur in groups of widely dispersed size. This paper models collective action problems as two-strategy multiplayer games and studies the effect of variability in group size on the evolution of cooperative behavior under the replicator dynamics. The analysis identifies elementary conditions on the payoff structure of the game implying that the evolution of cooperative behavior is promoted or inhibited when the group size experienced by a focal player is more or less variable. Similar but more stringent conditions are applicable when the confounding effect of size-biased sampling, which causes the group-size distribution experienced by a focal player to differ from the statistical distribution of group sizes, is taken into account.

Incorporating the information from direct and indirect neighbors into fitness evaluation enhances the cooperation in the social dilemmas

We propose an improved fitness evaluation method to investigate the evolution of cooperation in the spatial social dilemmas. In our model, a focal player’s fitness is calculated as the linear combination of his own payoff, the average payoffs of direct and indirect neighbors in which two independent selection parameters (α and β) are used to control the proportion of various payoff contribution to the current fitness. Then, the fitness-based strategy update rule is still Fermi-like, and asynchronous update is adopted here. A large plethora of numerical simulations are performed to validate the behaviors of the current model, and the results unambiguously demonstrate that the cooperation level is greatly enhanced by introducing the payoffs from the surrounding players. In particular, the influence of direct neighbors become more evident when compared with indirect neighbors since the correlation between focal players and their direct neighbors is much closer. Current outcomes are significant for us to further illustrate the origin and emergence of cooperation within a wide variety of natural and man-made systems.

Output Agreement Mechanisms and Common Knowledge

The recent advent of human computation -- employing non-experts to solve problems -- has inspired theoretical work in mechanism design for eliciting information when responses cannot be verified. We study a popular practical method, output agreement, from a theoretical perspective. In output agreement, two agents are given the same inputs and asked to produce some output; they are scored based on how closely their responses agree. Although simple, output agreement raises new conceptual questions. Primary is the fundamental importance of common knowledge: We show that, rather than being truthful, output agreement mechanisms elicit common knowledge from participants. We show that common knowledge is essentially the best that can be hoped for in any mechanism without verification unless there are restrictions on the information structure. This involves generalizing truthfulness to include responding to a query rather than simply reporting a private signal, along with a notion of common-knowledge equilibria. A final important issue raised by output agreement is focal equilibria and player computation of equilibria. We show that, for eliciting the mean of a random variable, a natural player inference process converges to the common-knowledge equilibrium; but this convergence may not occur for other types of queries.