The effect of asymmetric payoff mechanism on evolutionary networked prisoner’s dilemma game

In social and biological systems, there are obvious individual divergence and asymmetric payoff phenomenon due to the strength, power and influence differences. In this paper, we introduce an asymmetric payoff mechanism to evolutionary Prisoner’s Dilemma Game (PDG) on scale-free networks. The co-effects of individual diversity and asymmetric payoff mechanism on the evolution of cooperation and the wealth distribution under different updating rules are investigated. Numerical results show that the cooperation is highly promoted when the hub nodes are favored in the payoff matrix, which seems to harm the interest of the majority. But the inequality of social wealth distribution grows with the unbalanced payoff rule. However, when the node difference is eliminated in the learning strategy, the asymmetric payoff rule will not affect the cooperation level. Our work may sharpen the understanding of the cooperative behavior and wealth inequality in the society.     

Cooperative Dynamics in Lattice-Embedded Scale-Free Networks

We investigate cooperative behaviors of lattice-embeddedscale-free networking agents in the prisoner's dilemma game model byemploying two initial strategy distribution mechanisms, which are specificdistribution to the most connected sites (hubs) and random distribution. Ourstudy indicates that the game dynamics crucially depends on the underlyingspatial network structure with different strategy distribution mechanism.The cooperators' specific distribution contributes to an enhanced level ofcooperation in the system compared with random one, and cooperation isrobust to cooperators' specific distribution but fragile to defectors' specific distribution. Especially, unlike the specific case, increasing heterogeneity of network does not always favor the emergence of cooperation under random mechanism. Furthermore, we study the geographical effects and find that the graphically constrained network structure tends to improve the evolution of cooperation in random case and in specific one for a large temptation to defect.     

Benefit community promotes evolution of cooperation in prisoners' dilemma game

Exploring the emergence and maintenance of cooperation in social dilemma is valuable and it arises considerable concerns of many researchers. In this paper, we propose a mechanism to promote cooperation, called benefit community,in which cooperators linking together form a common benefit community and all their payoffs obtained from game are divided coequally. The robustness of conclusions is tested for the PDG(prisoners' dilemma game) on square lattice and WS small world network. We find that cooperation can be promoted by this typical mechanism, especially, it can diffuse and prevail more easily and rapidly on the WS small world network than it on the square lattice, even if a big temptation to defect b. Our research provides a feasible direction to resolve the social dilemma.     

Defect equilibria and conduction mechanisms in ice

Dielectric and elastic relaxation processes in ice may be explained by means of two types of point defects. At the crossover they interchange their roles as majority and minority mechanism. From conductivity measurements at the crossover it is possible to determine the defect mobilities, without knowing the effective charges. Measurements from different laboratories lead to the same results and to the conclusion that in contrast to earlier theoretieal ideas the ion states as such do not play an essential role in the Debye relaxation. The two mechanisms responsible for this process are Bjerrum defects as envisaged in earlier concepts and Bjerrum-ion aggregates. These defects allow an explanation of the temperature dependence of the conductivity in pure and doped ice.     

Adjusting learning motivation to promote cooperation

An evolutionary prisoner’s dilemma game with players adjusting their learning motivation is studied. At each time step, each player can adjust his/her learning motivation according to the difference between the current payoff and payoff aspiration. Greater payoff aspiration means stronger learning motivation, and vice versa. We find that the density of cooperation in a spatial prisoner’s dilemma game is enhanced when the learning motivation mechanism is considered. Meanwhile, we show that proper noise can not only induce the highest cooperation level but also can maintain the cooperation phenomenon even though there is more temptation to defect.     

The Polarization of the Coupling Strength of Interdependent Networks Stimulates Cooperation

We introduce a mixed network coupling mechanism and study its effects on how cooperation evolves in interdependent networks. This mechanism allows some players (conservative-driven) to establish a fixed-strength coupling, while other players (radical-driven) adjust their coupling strength through the evolution of strategy. By means of numerical simulation, a hump-like relationship between the level of cooperation and conservative participant density is revealed. Interestingly, interspecies interactions stimulate polarization of the coupling strength of radical-driven players, promoting cooperation between two types of players. We thus demonstrate that a simple mixed network coupling mechanism substantially expands the scope of cooperation among structured populations.     

Friction at the mesoscale

The organization of structures at the mesoscale is assumed to be the most important mechanism for the majority of friction types. Evidence is provided for the hypothesis that defect organization is fundamental to both tribological and internal friction.     

A 2-stage strategy updating rule promotes cooperation in the prisoner's dilemma game

In this study,we propose a spatial prisoner’s dilemma game model with a 2-stage strategy updating rule,and focus on the cooperation behavior of the system.In the first stage,i.e.,the pre-learning stage,a focal player decides whether to update his strategy according to the pre-learning factor β and the payoff difference between himself and the average of his neighbors.If the player makes up his mind to update,he enters into the second stage,i.e.,the learning stage,and adopts a strategy of a randomly selected neighbor according to the standard Fermi updating rule.The simulation results show that the cooperation level has a non-trivial dependence on the pre-learning factor.Generally,the cooperation frequency decreases as the pre-learning factor increases;but a high cooperation level can be obtained in the intermediate region of 3 < β < 1.We then give some explanations via studying the co-action of pre-learning and learning.Our results may sharpen the understanding of the influence of the strategy updating rule on evolutionary games.     

Photo-magneto-electric effect in semi-insulating GaAs: carrier lifetimes and influence of the defect structure

We report the investigation of the Photo-Magneto-Electric effect (PME) in semi-insulating Liquid-Encapsulated (LEC-) grown GaAs crystals, using both intrinsic and impurity excitation. The role of the majority and minority carriers on the conductivity phenomena was evaluated and the lifetimes of electrons and holes were determined depending on excitation conditions. Anomalously high PME voltages, reaching in some cases some volts, were measured, which demonstrate a sharp drop in the temperature region 320–360K. The observed changes are discussed supposing that the influence of the non-homogeneous defect structure of the samples is essential.     

Coevolution of game and network structure with adjustable linking

Most papers about the evolutionary game on graph assume the statistic network structure. However, in the real world, social interaction could change the relationship among people. And the change of social structure will also affect people’s strategies. We build a coevolution model of prisoner’s dilemma game and network structure to study the dynamic interaction in the real world. Differing from other coevolution models, players rewire their network connections according to the density of cooperation and other players’ payoffs. We use a parameter α to control the effect of payoff in the process of rewiring. Based on the asynchronous update rule and Monte Carlo simulation, we find that, when players prefer to rewire their links to those who are richer, the temptation can increase the cooperation density.     

Evolutionary prisoner’s dilemma game in flocks

We investigate an evolutionary prisoner’s dilemma game among self-driven agents, where collective motion of biological flocks is imitated through averaging directions of neighbors. Depending on the temptation to defect and the velocity at which agents move, we find that cooperation can not only be maintained in such a system but there exists an optimal size of interaction neighborhood, which can induce the maximum cooperation level. When compared with the case that all agents do not move, cooperation can even be enhanced by the mobility of individuals, provided that the velocity and the size of neighborhood are not too large. Besides, we find that the system exhibits aggregation behavior, and cooperators may coexist with defectors at equilibrium.     

Prisoner's Dilemma Game on Clustered Scale-Free Networks under Different Initial Distributions

The evolutionary prisoner＇s dilemma game is investigated under different initial distributions for cooperators and defectors on scale-free networks with a tunable clustering coefficient. It is found that, on the one hand, cooperation can be enhanced with the increasing clustering coefficient when only the most connected nodes are occupied by cooperators initially. On the other hand, if cooperators just occupy the lowest-degree nodes at the beginning, then the higher the value of the clustering coefficient, the more unfavorable the environment for cooperators to survive for the increment of temptation to defect. Thereafter, we analytically argue these nontrivial phenomena by calculating the cooperation probability of the nodes with different degrees in the steady state, and obtain the critical values of initial frequency of cooperators below which cooperators would vanish finally for the two initial distributions.     

Spatial Games Based on Pursuing the Highest Average Payoff

We propose a strategy updating mechanism based on pursuing the highest average payoff to investigate the prisoner＇s dilemma game and the snowdrift game. We apply the new rule to investigate cooperative behaviours on regular, small-world, scale-free networks, and find spatial structure can maintain cooperation for the prisoner＇s dilemma game. fn the snowdrift game, spatial structure can inhibit or promote cooperative behaviour which depends on payoff parameter. We further study cooperative behaviour on scale-free network in detail. Interestingly, non-monotonous behaviours observed on scale-free network with middle-degree individuals have the lowest cooperation level. We also find that large-degree individuals change their strategies more frequently for both games.     

Effects of the planarity and heterogeneity of networks on evolutionary two-player games

We study the effects of the planarity and heterogeneity of networks on evolutionary two-player symmetric games by considering four different kinds of networks, including two types of heterogeneous networks: the weighted planar stochastic lattice(a planar scale-free network) and the random uncorrelated scale-free network with the same degree distribution as the weighted planar stochastic lattice; and two types of homogeneous networks: the hexagonal lattice and the random regular network with the same degree k_0= 6 as the hexagonal lattice. Using extensive computer simulations, we found that both the planarity and heterogeneity of the network have a significant influence on the evolution of cooperation, either promotion or inhibition, depending not only on the specific kind of game(the Harmony, Snowdrift, Stag Hunt or Prisoner's Dilemma games), but also on the update rule(the Fermi, replicator or unconditional imitation rules).     

Modelling Moran Process with Network Dynamics for the Evolution of Cooperation

We introduce a simple model based on the Moran process with network dynamics. Using pair approximation, the cooperation frequencies at equilibrium states are deduced for general interactions. Three usual social dilemmas are discussed in the framework of our model. It is found that they all have a phase transition at the same value of cost-to-benefit ratio. For the prisoner＇s dilemma game, notably it is exactly the simple rule reported in the literature [Nature 441 （2006） 502]. In our model, the simple rule results from the parent-offspring link. Thus the basic mechanism for cooperation enhancement in network reciprocity is in line with the Hamilton rule of kin selection. Our simulations verify the analysis obtained from pair approximation.     

Impacts of memory on a regular lattice for different population sizes with asynchronous update in spatial snowdrift game

Memory is an important factor on the evolution of cooperation in spatial structure. For evolutionary biologists, the problem is often how cooperation acts can emerge in an evolving system. In the case of snowdrift game, it is found that memory can boost cooperation level for large cost-to-benefit ratio r, while inhibit cooperation for small r. Thus, how to enlarge the range of r for the purpose of enhancing cooperation becomes a hot issue recently. This paper addresses a new memory-based approach and its core lies in: Each agent applies the given rule to compare its own historical payoffs in a certain memory size, and take the obtained maximal one as virtual payoff. In order to get the optimal strategy, each agent randomly selects one of its neighbours to compare their virtual payoffs, which can lead to the optimal strategy. Both constant-size memory and size-varying memory are investigated by means of a scenario of asynchronous updating algorithm on regular lattices with different sizes. Simulation results show that this approach effectively enhances cooperation level in spatial structure and makes the high cooperation level simultaneously emerge for both small and large r. Moreover, it is discovered that population sizes have a significant influence on the effects of cooperation.     

Continuous spatial public goods game with self and peer punishment based on particle swarm optimization

How cooperative behavior emerges and evolves in human society remains a puzzle. It has been observed that the sense of guilt rooted from free-riding and the sense of justice for punishing the free-riders are prevalent in the real world. Inspired by this observation, two punishment mechanisms have been introduced in the spatial public goods game which are called self-punishment and peer punishment respectively in this paper. In each situation, we have introduced a corresponding parameter to describe the level of individual tolerance or social tolerance. For each individual, whether to punish others or whether it will be punished by others depends on the corresponding tolerance parameter. We focus on the effects of the two kinds of tolerance parameters on the cooperation of the population. The particle swarm optimization (PSO)-based learning rule is used to describe the strategy updating process of individuals. We consider both of the memory and the imitation in our model. Via simulation experiments, we find that both of the two punishment mechanisms could facilitate the promotion of cooperation to a large extent. For the self-punishment and for most parameters in the peer punishment, the smaller the tolerance parameter, the more conducive it is to promote cooperation. These results can help us to better understand the prevailing phenomenon of cooperation in the real world.     

Fitness of others' evaluation effect promotes cooperation in spatial public goods game

Payoff-driven strategy updating rule has always been adopted as a classic mechanism, but up to now, there have been a great many of researches on considering other forms of strategy updating rules, among which pursuing high fitness is one of the most direct and conventional motivations in the decision-making using game theory. But there are few or no researches on fitness from the perspective of others' evaluation. In view of this, we propose a new model in which the evaluation effect with fitness-driven strategy updating rule is taken into consideration, and introduce an evaluation coefficient to present the degree of others' evaluation on individual's behavior. The cooperative individuals can get positive evaluation, otherwise defective individuals get negative evaluation, and the degree of evaluation is related to the number of neighbors who have the same strategy of individual. Through numerical simulation, we find that the evaluation effect of others can enhance the network reciprocity, thus promoting the cooperation. For a strong dilemma, the higher evaluation coefficient can greatly weaken the cooperation dilemma; for a weak one, the higher evaluation coefficient can make cooperator clusters spread faster, however, there is no significant difference in the level of cooperation in the final stable state among different evaluation coefficients. The cooperation becomes more flourish as the number of fitness-driven individuals increases, when all individuals adopt fitness-driven strategy updating rule, the cooperators can quickly occupy the whole population. Besides, we demonstrate the robustness of the results on the WS small-world network, ER random network, and BA scale-free network.     

双复杂网络间的演化博弈

复杂网络的演化博弈是社会结构与稳定的重要模型. 基于单网络演化博弈模型, 提出了一种双复杂动态网络的演化博弈模型, 考虑双复杂网络在两个不同收益矩阵的囚徒困境博弈下增长, 当两个网络没有相互联系时, 发现增长网络中的空间互利性所导致的平均合作水平的突变, 推广了前人的结论. 在两个网络有相互联系时, 平均合作水平可以两者出现高度同步. 在网络的收益系数达到一定时, 才实现较高的合作水平. 增加网络内连接数量时, 自然选择不利于网络的合作, 而公平选择却有利于网络的合作, 说明了更新策略的影响. 当增加网络间连接数量时, 两个网络合作水平都下降. 当保持网络间和网络内的连接比例不变时, 网络的平均度越大, 平均合作水平越小. 本文发现了背叛领袖的存在, 并揭示了双网络模型下背叛领袖对平均合作水平的影响及其与合作领袖的互动机理, 这结果给出社会结构, 稳定和演化的重要信息和启示.     

碳纳米管中点缺陷对热导率影响的正交试验模拟分析

在碳纳米管的制备过程中, 各种点缺陷不可避免地存在于其晶格结构中, 对于碳管的热输运性质造成不可忽视的影响. 使用非平衡分子动力学方法, 选用反应经验键序势能, 模拟计算含有缺陷的碳纳米管的热导率. 尝试采用正交试验方法设计算例, 不但减少了计算量, 并且利于分析缺陷类型、 管长和管径三种结构因素对缺陷造成的热导率下降影响的主次和趋势. 重点研究了掺杂、 吸附和空位三类点缺陷的影响, 与无缺陷完整碳纳米管进行比较, 开展缺陷效应分析, 并进一步考察了环境温度等因素的影响. 模拟结果表明, 相对完整无缺陷碳管, 含有点缺陷的碳管热导率显着下降; 在有缺陷存在的情况下, 缺陷的类型对碳管热导率的影响最大, 管径次之, 管长影响相对最小; 缺陷类型对热导率影响力从大到小依次为: 空位 > 掺杂 > 吸附; 不同环境温度下, 点缺陷对碳管热导率的影响不尽相同.