Synergy punishment promotes cooperation in spatial public good game

Liu, Jinzhuo; Meng, Haoran; Wang, Wei; Li, Tong; Yu, Yong

doi:10.1016/j.chaos.2018.01.019

Cited by 41 publications

(15 citation statements)

References 30 publications

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“…It is found that this kind of network structure plays an important role in the evolution of cooperation. In addition, a large number of mechanisms of promoting cooperation have been recently proposed by considering the social factor, such as rewards and punishments [22,23], reputation [24], aspiration [25], tolerance [26], teaching activity [27], memory [28][29][30], emotion [31][32][33], rationality [34,35], restructuring partnership [36], migration [37] and so forth. Additionally, interdependent networks have been considered to be a more suitable framework for the investigation of networked cooperative dynamics, and seemingly insignificant factors in one network can lead to the extraordinary consequences in another network [38][39][40].…”

Section: Introductionmentioning

confidence: 99%

Degree of satisfaction-based adaptive interaction in spatial Prisoner’s dilemma

Dang

Zhang

et al. 2022

Nonlinear Dyn

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To study why the altruistic cooperation behavior can emerge and maintain among egoistical individuals, researchers across several disciplines have made great contributions for the solutions of this fascinating problem. Ordinarily, the spatial structure is a most-often used framework to investigate the cooperative dynamics of evolutionary game. However, very few researchers take into account the reaction of evolutionary game dynamics to interactive intensity between individuals. On account of this, we propose a computational model of automatic adjustment the interactive intensity based on individual's degree of satisfaction to study the iterated prisoner's dilemma game in a twodimensional square lattice. In this model, selfish individual considers whether the benefits obtained from the other party satisfies its own requirements to determine the intensity of interaction from it to the other party. More specifically, the interactive intensity from an individual x to its some neighbor y is driven by the relations between x obtained current benefit from y (denoted by P x⇀y ) and x's satisfaction payoff (denoted by S p ). If P x⇀y > S p , x will increase the intensity of interaction from itself to y; On the contrary, if P x⇀y < S p , x will weaken the intensity of interaction; Other scenario remain the same. Simulation results show that the proposed mechanism can effectively promote the emergence and maintain of cooperation in population, and the satisfying coefficient α (0 < α < 1) plays an essential role on

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Section: Introductionmentioning

confidence: 99%

Degree of satisfaction-based adaptive interaction in spatial Prisoner’s dilemma

Dang

Zhang

et al. 2022

Nonlinear Dyn

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“…Without exaggeration, hundreds of research papers were published by scientists with biology, economics, applied mathematics, or statistical physics background, in which they proposed different microscopic models to increase the general willingness of actors to cooperate with their partners [8,9,10,11,12]. In some cases the desired evolutionary outcome is expected, for example when defection is punished or cooperation is awarded by individuals or by a governing institution [13,14,15,16,17,18,19]. In these cases, however, the proper question is how to avoid the so-called secondorder free-riding, when a cooperator player is reluctant to contribute and maintain the mentioned cooperation supporting institution or behavior [20,21,22,23].…”

Section: Introductionmentioning

confidence: 99%

The self-organizing impact of averaged payoffs on the evolution of cooperation

Szolnoki,

Perc

2021

Preprint

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According to the fundamental principle of evolutionary game theory, the more successful strategy in a population should spread. Hence, during a strategy imitation process a player compares its payoff value to the payoff value held by a competing strategy. But this information is not always accurate. To avoid ambiguity a learner may therefore decide to collect a more reliable statistics by averaging the payoff values of its opponents in the neighborhood, and makes a decision afterwards. This simple alteration of the standard microscopic protocol significantly improves the cooperation level in a population. Furthermore, the positive impact can be strengthened by increasing the role of the environment and the size of the evaluation circle. The mechanism that explains this improvement is based on a self-organizing process which reveals the detrimental consequence of defector aggregation that remains partly hidden during face-to-face comparisons. Notably, the reported phenomenon is not limited to lattice populations but remains valid also for systems described by irregular interaction networks.

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“…With the development of evolutionary game, the influence of different network structures on cooperative behavior has been investigated, such as small-world networks 14,15 , scale-free networks 16,17 and interdependent networks 18 . In addition, many mechanisms have been proposed to promote cooperation, such as neighborhood diversity 19 , environmental factor 20 , link weight 21,22 , reputation 23 , punishment 24 and reward 25 , etc. Memory effect also attracts many scholars' attention [26][27][28] . In the spatial cooperation evolution model proposed by Nowak, the next step strategy of game individuals is determined by the payoff of the current time step.…”

Section: Introductionmentioning

confidence: 99%

Research on the impact of payoff reflection mechanism on cooperation evolution

Wang

Sheng

et al. 2020

Preprint

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Taking into account the results of historical behavior in real life on the choice of strategy, we proposes a payoff reflection mechanism. In the process of cooperation evolution, the game individuals will judge whether to learn each other's strategies based on the historical payoff of himself and his neighbors, that is, the strategy learning is affected by the historical payoff. If the current strategy can bring greater payoff in historical behavior, the game players will change the current strategy with less possibility. For this reason, the historical payoff reference coefficients w and u of the game individuals and their neighbors are proposed to measure the degree of reference of game individuals to their own and neighbors' historical payoff. The memory interval length is expressed by M. The experimental results show that the payoff reflection mechanism can greatly improve the cooperation level of the group. However, the reference rate of historical payoff is not the bigger the better. The strength of memory ability and the level of betrayal temptation will affect the optimal value of w and u.

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Synergy punishment promotes cooperation in spatial public good game

Cited by 41 publications

References 30 publications

Degree of satisfaction-based adaptive interaction in spatial Prisoner’s dilemma

Degree of satisfaction-based adaptive interaction in spatial Prisoner’s dilemma

The self-organizing impact of averaged payoffs on the evolution of cooperation

Research on the impact of payoff reflection mechanism on cooperation evolution

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