Tolerance-based punishment in continuous public goods game

Altruistic punishment for defectors is considered as a key motive for the explanation of cooperation. However, there is no clear border between the cooperative and defective behaviors in a continuous strategy game. We propose a model to study the effect of punishment on the evolution of cooperation in continuous public goods game, wherein individuals have the traits to punish the co-players based on social tolerance. We show that a reasonable punishment with a uniform tolerance can spur individuals to make more investments. Additionally, for a fixed punishment cost and a fixed fine, a moderate value of tolerance can result in the best promotion of cooperation. Furthermore, we investigate the coevolutionary dynamics of investment and tolerance. We find that the population splits into two branches: high-tolerance individuals who make high investments and low-tolerance individuals who make low investments. A dynamic equilibrium is achieved between these two types of individuals. Our work extends punishment to continuous cooperative behaviors and the results may enhance the understanding of altruistic punishment in the evolution of human cooperation.     

Memory-based evolutionary game on small-world network with tunable heterogeneity

Most papers about evolutionary games on graph assume agents have no memory. Yet, in the real world, interaction history can also affect an agent’s decision. So we introduce a memory-based agent model and investigate the Prisoner’s Dilemma game on a Heterogeneous Newman-Watts small-world network based on a Genetic Algorithm, focusing on heterogeneity’s role in the emergence of cooperative behaviors. In contrast with previous results, we find that a different heterogeneity parameter domain range imposes an entirely different impact on the cooperation fraction. In the parameter range corresponding to networks with extremely high heterogeneity, the decrease in heterogeneity greatly promotes the proportion of cooperation strategy, while in the remaining parameter range, which relates to relatively homogeneous networks, the variation of heterogeneity barely affects the cooperation fraction. Also our study provides a detailed insight into the microscopic factors that contribute to the performance of cooperation frequency.     

Evolution of cooperation in a heterogeneous population with influential individuals

Influential individuals are introduced and integrated with the public goods game (PGG) to investigate their influence on the emergence and evolution of cooperation. In the model, some influential individuals whose behaviors can be controlled by us are introduced into a homogeneous population on a square lattice. The influential individuals can play three kinds of roles: I. exemplar, II. supervisor with the power to punish defectors, and III. supervisor with the power to reward cooperative co-players. It is found that the existence of influential individuals who play Role I turns out to be detrimental to cooperation and that the larger the number of influential individuals is, the more difficult it is for cooperation to be maintained. For those playing supervisory roles, both punishment and reward are found to be effective ways for the influential individuals to promote and stabilize cooperative behavior. By comparing the critical costs and the mean payoffs for a low multiplication factor under the role of punishment and the role of reward, it is found that reward is a more effective intervention measure than punishment for influential individuals seeking to improve cooperation and that reward leads to a higher mean payoff.     

An Improved Fitness Evaluation Mechanism with Memory in Spatial Prisoner's Dilemma Game on Regular Lattices

To deeply understand the emergence of cooperation in natural,social and economical systems,we present an improved fitness evaluation mechanism with memory in spatial prisoner's dilemma game on regular lattices.In our model,the individual fitness is not only determined by the payoff in the current game round,but also by the payoffs in previous round bins.A tunable parameter,termed as the memory strength(μ),which lies between 0 and 1,is introduced into the model to regulate the ratio of payoffs of current and previous game rounds in the individual fitness calculation.When μ = 0,our model is reduced to the standard prisoner's dilemma game;while μ = 1 represents the case in which the payoff is totally determined by the initial strategies and thus it is far from the realistic ones.Extensive numerical simulations indicate that the memory effect can substantially promote the evolution of cooperation.For μ 1,the stronger the memory effect,the higher the cooperation level,but μ = 1 leads to a pathological state of cooperation,but can partially enhance the cooperation in the very large temptation parameter.The current results are of great significance for us to account for the role of memory effect during the evolution of cooperation among selfish players.     

Clustering Effect on the Evolution of Cooperation in a Herding Snowdrift Game

We study the evolution of cooperation for two cluster breaking mechanisms in a herding snowdrift game. The cooperative behavior is observed to be related to the duster size. A negative dependence of the payoff parameter r on cooperative behavior is discovered. For a low r, herding helps promote the cooperation, whereas for a high r, herding tends to prevent cooperative behavior.     

The coevolution of partner switching and strategy updating in non-excludable public goods game

Spatial public goods game is a popular metaphor to model the dilemma of collective cooperation on graphs, yet the non-excludable property of public goods has seldom been considered in previous models. Based upon a coevolutionary model where agents play public goods games and adjust their partnerships, the present model incorporates the non-excludable property of public goods: agents are able to adjust their participation in the games hosted by others, whereas they cannot exclude others from their own games. In the coevolution, a directed and dynamical network which represents partnerships among autonomous agents is evolved. We find that non-excludable property counteracts the positive effect of partner switching, i.e., the equilibrium level of cooperation is lower than that in the situation of excludable public goods game. Therefore, we study the effect of individual punishment that cooperative agents pay a personal cost to decrease benefits of those defective neighbors who participate in their hosted games. It is found that the cooperation level in the whole population is heightened in the presence of such a costly behavior.     

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.     

Stochastically Stable Globally Coupled Maps with Bistable Thermodynamic Limit

We study systems of globally coupled interval maps, where the identical individual maps have two expanding, fractional linear, onto branches, and where the coupling is introduced via a parameter - common to all individual maps - that depends in an analytic way on the mean field of the system. We show: 1) For the range of coupling parameters we consider, finite-size coupled systems always have a unique invariant probability density which is strictly positive and analytic, and all finite-size systems exhibit exponential decay of correlations. 2) For the same range of parameters, the self-consistent Perron-Frobenius operator which captures essential aspects of the corresponding infinite-size system (arising as the limit of the above when the system size tends to infinity), undergoes a supercritical pitchfork bifurcation from a unique stable equilibrium to the coexistence of two stable and one unstable equilibrium.     

Heterogeneity of allocation promotes cooperation in public goods games

We investigate the effects of heterogeneous investment and distribution on the evolution of cooperation in the context of the public goods games. To do this, we develop a simple model in which each individual allocates differing funds to his direct neighbors based upon their difference in connectivity, because of the heterogeneity of real social ties. This difference is characterized by the weight of the link between paired individuals, with an adjustable parameter precisely controlling the heterogeneous level of ties. By numerical simulations, it is found that allocating both too much and too little funds to diverse neighbors can remarkably improve the cooperation level. However, there exists a worst mode of funds allocation leading to the most unfavorable cooperation induced by the moderate values of the parameter. In order to better reveal the potential causes behind these nontrivial phenomena we probe the microscopic characteristics including the average payoff and the cooperator density for individuals of different degrees. It demonstrates rather different dynamical behaviors between the modes of these two types of cooperation promoter. Besides, we also investigate the total link weights of individuals numerically and theoretically for negative values of the parameter, and conclude that the payoff magnitude of middle-degree nodes plays a crucial role in determining the cooperators’ fate.     

Effect of community structure on coevolutionary dynamics with dynamical linking

We investigate the effect of community structure on the evolution of cooperation in the prisoner’s dilemma and the snowdrift game with dynamical linking. We show both analytically and numerically that cooperators are generally more favorable on community networks than on networks without community structure, and in particular, there exists an optimal intermediate value of the model parameter leading to the easiest fixation of cooperators. We show that our results are robust with respect to the initial number of cooperators and are valid for a wide range of the ratio of time scales associated with linking and strategy dynamics. Since community structure is ubiquitous in real social networks, our results may provide new insights into the evolution of cooperation in real world.     

Punishment Mechanism with Self-Adjusting Rules in Spatial Voluntary Public Goods Games

The phenomena of cooperation in animal and human society are ubiquitous, but the selfish outcome that no player contributes to the public good will lead to the "tragedy of the commons". The recent research shows that high punishment can improve the cooperation of the population. In this paper, we introduce a punishment mechanism into spatial voluntary public goods games with every individual only knowing his own payoff in each round. Using the self-adjusting rules, we find that the different cost for punishment can lead to different effects on the voluntary public goods games. Especially, when the cost for punishment is decreased, a higher contribution region will appear in the case of low r value. It means even for the low r value, individuals can form the contributing groups in large quantities to produce a more efficient outcome than that in moderate r value. In addition, we also find the players' memory can have effects on the average outcome of the population.     

Dynamic Evolution with Limited Learning Information on a Small-World Network

This paper investigates the dynamic evolution with limited learninginformation on a small-world network. In the system, the information amongthe interaction players is not very lucid, and the players are not allowedto inspect the profit collected by its neighbors, thus the focal playercannot choose randomly a neighbor or the wealthiest one and compare itspayoff to copy its strategy. It is assumed that the information acquaintedby the player declines in the form of the exponential with the geographicaldistance between the players, and a parameter V is introduced to denote theinspect-ability about the players. It is found that under the hospitableconditions, cooperation increases with the randomness and is inhibited bythe large connectivity for the prisoner's dilemma; however, cooperation ismaximal at the moderate rewiring probability and is chaos with theconnectivity for the snowdrift game. For the two games, the acuminous sightis in favor of the cooperation under the hospitable conditions; whereas, themyopic eyes are advantageous to cooperation and cooperation increases withthe randomness under the hostile condition.     

Quasiclassicality and Quantum Measurement

We address two problems arising in the quantum measurement process: A rigorous definition of quasiclassical systems and its implications for the observed collapse of the wave function. For a mathematical definition of quasiclassical systems, we recall the structure of models for the classical world. They describe the dynamics of some simultaneously measurable quantities, thereby ignoring many properties of the modeled real world phenomena, especially all quantum mechanical ones. In this article, we define a quasiclassical system as a quantum system which allows such a simplified modelling. By classifying such quasiclassical systems, it is shown that they naturally correspond to classical systems in the usual sense. By describing quantum measurements with the aid of quasiclassical systems, we then observe an effect that is similar to decoherence: While the latter implies that off-diagonal entries of the density matrix vanish, in the former they correspond to the parts of the system that are not modeled and thus can be ignored. Especially, they do not influence any measurements of the properties contained in the classical model. Mathematically, this allows to treat the output of a quantum measurement as a classical probability distribution. Finally, we discuss some implications of this definition of quasiclassicality on the interpretation of quantum mechanics.     

Evolution of cooperation among interacting individuals through molecular dynamics simulations

Using molecular dynamics (MD) simulation and evolutionary game theory, we incorporate the spacial structure of individuals into the study of the behaviors of cooperation, by adopting the prisoner's dilemma and snowdrift game as metaphors of cooperation between unrelated individuals. The results show that the introduction of spacial structure enhances cooperation using the strategy of prisoner's dilemma while does not make much changes to the cooperation if the strategy of snowdrift game is used. It is also found that our model is a meta-phase between regular ring graph model and complex network model. And the “activity of players” T^* we introduced makes our simulation much more closer to real world problems.     

Maintenance of cooperation induced by punishment in public goods games

In this paper, we study the public goods games with punishment by adopting the well-known approximate best response dynamics. It shows that the evolution of cooperation is affected by two aspects when other parameters are fixed. One is the punishment mechanism which can avoid the dilemma of lacking investment, and the other is the degree of rationality. Theoretical analysis and numerical results indicate that the existence of punishment mechanism and distribution of rationality are the keys to the enhancement of cooperation level. We also testify that they can heavily influence the payoffs of system as well. The findings in this paper may provide a deeper understanding of some social dilemmas.     

Promoting cooperation by local contribution under stochastic win-stay-lose-shift mechanism

We introduce a stochastic win-stay-lose-shift (WSLS) mechanism into evolutionary Prisoner’s Dilemma on small-world networks. At each time step, after playing with all its immediate neighbors, each individual gets a score to evaluate its performance in the game. The score is a linear combination of an individual’s total payoff (i.e., individual gain from the group) and local contribution to its neighbors (i.e., individual donation to the group). If one’s actual score is not larger than its desired score aspiration, it switches current strategy to the opposite one with the probability depending on the difference between the two scores. Under this stochastic WSLS regime, we assume that each focal individual gains its fixed score aspiration under the condition of full cooperation in its neighborhood, and find that cooperation is significantly enhanced under some certain parameters of the model by studying the evolution of cooperation. We also explore the influences of different values of learning rate and intensity of deterministic switch on the evolution of cooperation. Simulation results show that cooperation level monotonically increases with the relative weight of the local contribution to the score. For much low intensity of deterministic switch, cooperation is to a large extent independent of learning rate, and full cooperation can be reached when relative weight is not less than 0.5. Otherwise, cooperation level is affected by the value of learning rate. Besides, we find that the cooperation level is not sensitive to the topological parameters. To explain these simulation results, we provide corresponding analytical results based on mean-field approximation, and find out that simulation results are in close agreement with the analytical ones. Our work may be helpful in understanding the cooperative behavior in social systems based on this stochastic WSLS mechanism.     

Effects of Inertia on Evolutionary Prisoner's Dilemma Game

Considering the inertia of individuals in real life, we propose a modified Fermi updating rule, where the inertia of players is introduced into evolutionary prisoner's dilemma game (PDG) on square lattices. We mainly focus on how the inertia affects the cooperative behavior of the system. Interestingly, we find that the cooperation level has a nonmonotonic dependence on the inertia: with small inertia, cooperators will soon be invaded by defectors; with large inertia, players are unwilling to change their strategies and the cooperation level remains the same as the initial state; while a moderate inertia can induce the highest cooperation level. Moreover, effects of environmental noise and individual inertia are studied. Our work may be helpful in understanding the emergence and persistence of cooperation in nature and society.     

Effects of Inertia on Evolutionary Prisoner's Dilemma Game

Considering the inertia of individuals in real life,we propose a modified Fermi updating rule,where the inertia of players is introduced into evolutionary prisoner's dilemma game(PDG) on square lattices.We mainly focus on how the inertia affects the cooperative behavior of the system.Interestingly,we find that the cooperation level has a nonmonotonic dependence on the inertia:with small inertia,cooperators will soon be invaded by defectors;with large inertia,players are unwilling to change their strategies and the cooperation level remains the same as the initial state;while a moderate inertia can induce the highest cooperation level.Moreover,effects of environmental noise and individual inertia are studied.Our work may be helpful in understanding the emergence and persistence of cooperation in nature and society.     

Parameter Diversity Induced Multiple Spatial Coherence Resonances and Spiral Waves in Neuronal Network with and Without Noise

Diversity in the neurons and noise are inevitable in the real neuronal network. In this paper, parameter diversity induced spiral waves and multiple spatial coherence resonances in a two-dimensional neuronal network without or with noise are simulated. The relationship between the multiple resonances and the multiple transitions between patterns of spiral waves are identified. The coherence degrees induced by the diversity are suppressed when noise is introduced and noise density is increased. The results suggest that natural nervous system might profit from both parameter diversity and noise, provided a possible approach to control formation and transition of spiral wave by the cooperation between the diversity and noise.