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Highlight • The result exists an obvious piecewise phenomenon for individual's aspiration level on promoting cooperation Abstract In real life, everyone is full of yearning and pursuit for future life. The difference between reality and ideals encourage people to constantly adjust the current state, so that they can better adapt to changes in the surrounding environment. Thus, we propose a spatial prisoner's dilemma game model where individuals have expectation towards the payoff obtained from nearest neighbors, and individuals can adaptively adjust their update willingness based on the satisfaction of income. Through numerical calculation, we find that different b values will have an appropriate aspiration level to promote cooperation. In addition, the results have an obvious phase transition phenomenon for individual's aspiration level on promoting cooperation. Moreover, only moderate aspiration level can promote the evolution of cooperative behavior, due to it can lead to the heterogeneous distribution of update willingness, which will be beneficial to the evolution of cooperation. [ABSTRACT FROM AUTHOR]

Abstract In real world, cooperation among unrelated agents remains to represent one open challenge in many disciplines. In some cases, subjects can even change their social dilemmas to ensure their own benefit. Inspired by this fact, here we propose a multigame (composed of prisoner's dilemma game and snowdrift game) and its coevolution mechanism in networked populations: if a player succeeds to study the strategy of its opponent, it also learns the game type of its opponent. Based on numerous computation simulations, it is unveiled that compared with the setup of multigame, coevolution mechanism can effectively resolve the problem of collective cooperation. While for this observation, it is attributed to the fact that vast majority of players changed their games to snowdrift game (i.e. lower social dilemma), where cooperation-defection bistable state guarantees cooperation clusters. We hope our finding can inspire more studies for resolving the social dilemmas. [ABSTRACT FROM AUTHOR]

• This paper introduces expectation-based reinforcement learning methods in the public goods game. • The results under total population density show that individuals behavior exhibits conditional cooperation and its variant moody conditional cooperation. • In the network with empty nodes, conditional cooperation shows opposite trends. In social dilemmas, individual behavior generally follows the characteristics of conditional cooperation and emotional conditional cooperation. However, it is hard to adequately explain the behavior patterns of conditional cooperation with the evolutionary game theory. This paper introduces expectation-based reinforcement learning methods in the public goods game to investigate and account for the behavior patterns. Instead of letting individuals occupy the entire network as previous studies have done, we focus on studying individual behavior patterns on a network with empty nodes. The results under total population density show the effectivity of our model as they are consistent with those of the previous studies, that is, individuals' behavior exhibits conditional cooperation and its variant moody conditional cooperation. However, in the network with empty nodes, conditional cooperation shows opposite trends. We finally demonstrate that an appropriate population density can facilitate the maintenance and development of cooperation. [ABSTRACT FROM AUTHOR]

We investigate the ability-based fitness calculation in an asymmetric setup to the evolution of cooperation on square lattice. In particular, if players can maintain its strategy for a round, then its abilities will increase 1, otherwise, its ability will turn to 0. We also assume that if players' abilities exceed a certain threshold M , then its environment is integrated into its fitness calculation via a simple parameter α. Through extensive numerical simulation, we find that large threshold M decreases cooperation, and large α, players' fitness is mainly decided by its dynamical environment, promotes cooperation. We also provide theoretical analysis and get the same results with simulation. Finally, we test its robustness on homogeneous random network and small-world network. Our work provides a deeper insight to network reciprocity. [ABSTRACT FROM AUTHOR]

• In this paper, we establish a two-layered multiplex network model which combines SIR epidemic process and vaccination decision-making. • We discover that imitating behavior would restrain the increase of herd immunity, • The model is verified by Monte Carlo simulations and mean-field equa- tions, respectively. • A suitable quantity of conformity motivated individual could be beneficial to save the social costs. When confronting the epidemics or pandemics, there often exists an interplay between epidemic incidence and the vaccination strategies of individuals. Recently, the characteristics of human behaviors, such as imitating nature or bandwagon effect, have been proven critical to the final herd immunity. In this paper, by establishing a two-layered multiplex network model which combines SIR epidemic process, vaccination decision-making and imitating human nature, we discover that imitating behavior would restrain the increase of herd immunity, which is verified by Monte Carlo simulations and mean-field equations, respectively. Interestingly, a suitable quantity of conformity motivated individual, counter-intuitively, could be beneficial to save the social costs. At the same time, we analytically determine the precise conditions for the minimum total social costs. The current results can help to understand the behavior of social group in depth and then explore public attitudes concerning the vaccine, which usually has a tremendous impact on social vaccine take-up within the population. [ABSTRACT FROM AUTHOR]

• We introduce third parties and disputants on interdependent network. • Disputants play prisoner's dilemma game and bring third parties extra payoffs. • Third parties intervene disputants play snowdrift dilemma game or not. • Conflicts in disputants are relieved though non-interventions exist in third party layer. Interventions from third parties, such as governmental agencies or organizations, play an important role in mitigating conflicts in modern human societies. The goal thereby is to pacify disputants, although this is subject to failure on account of self-interest from all involved. To study how relationships between disputants and third parties evolve, we propose an interdependent network model, where one layer is occupied by disputants and the other layer is occupied by third parties. Disputants play a prisoner's dilemma game, where defection is the dominant strategy, whereas third parties play a snowdrift game, where cooperation and defection coexist more commonly. Moreover, third parties have the ability to mediate a conflict on the other layer by enforcing a snowdrift game onto disputants, for which they can receive a fee. We show that third party interventions improve the evolution of cooperation between disputants, and also, that the improvement of cooperation in turn promotes interventions. Nonetheless, non-intervention does not go extinct, which enables defectors to survive, thus creating a feedback loop between the two networks layers. The evolutionary dynamics is characterized by fascinating spatial pattern formation, which we explore by means of Monte Carlo simulations and via replicator equations. [ABSTRACT FROM AUTHOR]

• a mechanism is proposed aiming to investigate the co-evolution of personal reputation and strategy under a general framework of interactive diversity. • Numerous simulations are conducted with sufficient analyses of the obtained results being followed. • The consideration of interaction diversity is able to ensure the maintenance of cooperation even if the temptation of adopting antisocial behavior (here, defection is considered) is relatively large. • Various discussions are performed in order to explain the reason of this effect from various perspectives, for instance, by counting the number of various chains and the evolution of clusters. In practice, there exists numerous examples indicating the phenomenon that individuals are inclined to employ different strategies when interacting with the others. This is incurred by the fact that individuals are able to adjust their strategies adaptively under different interacting environments. Scholars have devoted their efforts to this topic; nevertheless, the impact of diverse interactions on cooperation still needs to be further explored. In this manuscript, we propose a mechanism aiming to investigate the co-evolution of personal reputation and strategy under a general framework of interactive diversity (being referred to as edge-strategy for simplicity). Numerous simulations are conducted with sufficient analyses of the obtained results being provided. As illustrated by the evolutionary dynamics, we find that there exists an optimal reputation value which can promote the frequency of cooperation by a large extent. Furthermore, we can clearly conclude that the consideration of interaction diversity is able to ensure the maintenance of cooperation even if the temptation to adopt antisocial behavior is relatively large. Aiming to understand the phenomenon better, we also quantitatively analyze the results by investigating the statistics of interaction chain, cluster size and other microscopic information. Overall, we hope the findings here can provide some interesting insights in solving social dilemmas. [ABSTRACT FROM AUTHOR]

The emergence and maintenance of cooperation remains to be one of the overreaching problems and a number of scholars have devoted endless efforts to resolve such problems. To further explore this issue, we focus on the impact of heterogeneity of updating rules on cooperative behavior in voluntary prisoner's dilemma; here, two types of strategy updating rules are considered to mimic social facts which are listed as strategy learning mechanism and strategy teaching mechanism. The stability of different mechanisms on promoting cooperation is thoroughly investigated in this manuscript. Numerical simulations are conducted while corresponding results are presented with sufficient clarifications. We find that the strategy learning mechanism can promote cooperation steadily. However, with the variance in the proportion of the two update rules in the investigated community, the strategy teaching mechanism seems to be more sensitive. Moreover, compared with strategy learning mechanism, strategy teaching mechanism plays a more important and apparent role in promoting cooperation. We also find that personal strategy is sensitive to the varying of Loner's payoff σ, especially when σ is close to 1. We hope our findings will shed some lights on resolving the social dilemmas. [ABSTRACT FROM AUTHOR]

The question of resource allocation has been the focus issue in social and natural science. Should we narrow the gap between the rich and poor? Or should we increase the income inequality? Inspired by this matter, we propose a payoff redistribution model and explore which case can evaluate the cooperative level in public goods game. Specifically, we use a single parameter α to control the above two scenarios. Positive α increases the income inequality between rich and poor, while negative α ensures this equality and the case of α = 0 turns our model to the symmetric case, where there is no payoff redistribution effect. Extensive simulation shows that when we narrow the gap between the rich and poor, cooperation can be maintained, conversely, if this income inequality is increased, the cooperative groups are destroyed. Our work thus provides a novel clue to explore this problem especially from the viewpoint of evolutionary game theory. [ABSTRACT FROM AUTHOR]