一种基于势博弈的无线传感器网络拓扑控制算法

在实际的应用中,无线传感器网络常常由大量电池资源有限的传感器节点组成.如何降低网络功耗,最大化网络生存时间,是传感器网络拓扑控制技术的重要研究目标.随着传感节点的运行,节点的能量分布可能越来越不均衡,需要在考虑该因素的情况下,动态地调整节点的网络负载以均衡节点的能耗,达到延长网络生存时间的目的.该文引入博弈理论和势博弈的概念,综合考虑节点的剩余能量和节点发射功率等因素,设计了一种基于势博弈的拓扑控制模型,并证明了该模型纳什均衡的存在性.通过构造兼顾节点连通性和能耗均衡性的收益函数,以确保降低节点功耗的同时维持网络的连通性.通过提高邻居节点的平均剩余能量值以实现将剩余能量多的节点选择作为自身的邻居节点,提高节点能耗的均衡性.在此基础上,提出了一种分布式的能耗均衡拓扑控制算法.理论分析证明了该算法能保持网络的连通性.与现有基于博弈理论的DIA算法和MLPT算法相比,本算法形成的拓扑负载较重、剩余能量较小的瓶颈节点数量较少,节点剩余能量的方差较小,网络生存时间更长.     

一种优化无线传感器网络生命周期的容错拓扑研究

<正>由于无线传感器网络的节点能量受限,优化网络生命周期成为设计网络拓扑时首要考虑的问题.通过分析节点的剩余能量和负载量对节点生命周期的影响,提出了一种可延长无线传感器网络生命期的容错拓扑演化模型,并得出了在节点满足网络生存时间的条件下负载调节系数的取值范围.仿真实验结果表明,基于无标度网络的演化拓扑结构具有较好的容错性,并能够均衡网络节点能耗和延长网络生命周期.     

一种无线传感器网络簇间拓扑演化模型及其免疫研究

基于复杂网络理论, 研究由于节点失效所导致的无线传感器网络性能下降的问题, 提出一种新的簇间拓扑演化模型, 在此基础上讨论病毒的免疫策略, 并给出一种新的免疫机理. 理论分析表明, 该模型演化生成的网络不仅具有较强的容错性, 而且还可以有效避免节点因能量很快耗尽而过早死亡. 研究还发现, 对于网络全局信息未知的情况, 与随机免疫和熟人免疫策略相比, 本文所提免疫策略能够获得较好的免疫效果. 通过数值仿真对理论分析进行验证.     

具有异质增益因子的超图上的演化公共品博弈

近年来,空间结构和社会多样性对群体合作演化的影响吸引了人们极大的关注.本文在空间公共品博弈中引入了异质增益因子,研究超图上合作行为的演化.除所有博弈群组具有相同增益因子的原始模型外,还考虑了包括均匀分布、指数分布和幂律分布在内的不同异质性强度的三类异质增益因子分布.数值模拟结果显示,上述4种增益因子分布对应的公共品博弈中,均匀随机超图阶数g的增大有利于提高群体的合作水平.更进一步地,对比超图上原始空间公共品博弈的演化结果,群体中博弈群组增益因子异质性的引入能够显著促进群体的合作行为,幂律分布情况下能够使得系统获得最高合作水平.此外,研究了超边数目对群体合作演化的影响,结果表明上述结论对超边数目鲁棒,并且超边数目L的增大会抑制公共品博弈中合作行为的涌现.一定程度上,本文的研究结果有助于我们更好地理解超图上空间公共品博弈的演化动力学.     

开放式复杂航空网络系统的动力学演化

本文首先实证研究了中国航空网(CAN)与外部经济环境,即国民生产总值(GDP)的相关性,进而揭示CAN的演化方式及其拓扑特征的起源.发现自1998年起网络节点的度与其GDP成线性关系,表明了网络拓扑与经济因素有密切的联系,且CAN的度演化服从类似于多重过程(multiplicative process)的模式,而该模式又强烈依赖于GDP的增长率.这种独特的模式暗示了CAN具有类似适应度模型的微观机理.通过对演化方程的研究发现:1)CAN在增长过程中,节点加入的时刻具有经济上的偏好性,即节点加入的时刻与该节 关键词： 国民生产总值(GDP) 中国航空网(CAN) 双段幂率分布 多重过程     

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.     

基于复杂网络理论的微博用户关系网络演化模型研究

微博给人们提供便利的同时也产生了较大的负面影响.为获取微博谣言的传播规律,进而采取有效措施防控其传播,本文基于复杂网络理论研究微博用户关系网络的内部特征,提出一种微博用户关系网络演化模型,借助于平均场理论,分析该演化模型的拓扑统计特性,以及谣言在该演化模型上的传播动力学行为.理论分析和仿真实验表明,由该模型演化生成的微博用户关系网络具有无标度特性.度分布指数不仅与反向连接概率有关,而且还取决于节点的吸引度分布.研究还发现,与指数分布和均匀分布相比,当节点吸引度满足幂律分布时,稳态时的谣言传播程度较大.此外,随着反向连接概率或节点初始连边数量的增加,谣言爆发的概率以及网络中最终接受谣言的节点数量都会明显增大.     

基于无标度网络拓扑结构变化的舆论演化模型

基于BA无标度网络,构建了舆论和网络结构相互影响的自适应舆论演化模型.舆论的演化不仅受制于网络拓扑结构,而且也导致拓扑结构的变化.研究表明,演化达到稳态后,网络结构不再是初始的无标度网络而呈现泊松分布,而且随着时间的推移,系统中的舆论演化表现出很强的趋同效应,原来初始状态的几十个舆论,在长时间的演化后,大部分舆论灭亡,只有少数的舆论存留,且发展壮大.这种趋向与社会上的舆论、意见、信仰的演化大体上是符合的.     

一种新型二分网络类局域世界演化模型

现实世界中复杂网络的演化存在很明显的局域选择现象,然而目前关于二分网络中的局域世界演化模型研究较少．因此,本文建立了一个基于二分网络的类局域世界演化模型．首先定义了网络节点度值的饱和度．在此基础上提出了一种新型二分网络局域世界演化模型．新节点加入系统不需要全局知识,而是通过节点在网络演化的不同时刻度值饱和度为选择条件构造新节点的局域世界,然后利用择优连接从局域世界中选择节点增加连边完成网络演化．此类模型中新节点的局域世界是通过节点饱和度的限制被动生成,因此又称为类局域世界模型．通过模拟分析发现在节点度值饱和度的限制下择优连接并没有产生具有幂率特性的度分布,而是生成了度分布相对均匀的二分网络,即节点度值分布区间较小．此外,本文还给出了该网络的混合系数计算结果,该结果显示网络同配性与网络参数的选择有关,这一结果与网络邻点平均度的模拟结果一致．     

一类权重网络的加速演化模型

采用动态形成权重网络的方法，研究了在演化过程中新增边具有加速连接情况下权重网络的拓扑特性和强度分布，给出了节点强度与度的解析表达式.分析表明，加速演化的权重模型具有明显的无标度特性.再者，只要权重网络的边权重服从某一概率分布，则在演化过程中强度择优连接与度择优连接对于网络的度分布没有影响，且与具体的概率分布无关.     

Evolution of Cooperation in Public Goods Games

We investigate the evolution of cooperation with evolutionary public goods games based on finite populations, where four pure strategies: cooperators, efectors, punishers and loners who are unwilling to participate are considered. By adopting approximate best response dynamics, we show
that the magnitude of rationality not only quantitatively explains the experiment results in [Nature (London) {\bf 425} (2003) 390], but also it will heavily
influence the evolution of cooperation. Compared with previous results of infinite populations, which result in two equilibriums, we show that there merely exists a special equilibrium and the relevant high value of bounded rationality will sustain cooperation. In addition, we characterize that loner's payoff plays an active role in the maintenance of cooperation, which will only be warranted for the low and moderate values of loner's payoff. It thus indicates
the effects of rationality and loner's payoff will influence the cooperation. Finally, we highlight the important result that the introduction of voluntary participation and punishment will facilitate cooperation greatly.     

Coevolving agent strategies and network topology for the public goods games

Much of human cooperation remains an evolutionary riddle. Coevolutionary public goods games in structured populations are studied where players can change from an unproductive public goods game to a productive one, by evaluating the productivity of the public goods games. In our model, each individual participates in games organized by its neighborhood plus by itself. Coevolution here refers to an evolutionary process entailing both deletion of existing links and addition of new links between agents that accompanies the evolution of their strategies. Furthermore, we investigate the effects of time scale separation of strategy and structure on cooperation level. This study presents the following: Foremost, we observe that high cooperation levels in public goods interactions are attained by the entangled coevolution of strategy and structure. Presented results also confirm that the resulting networks show many features of real systems, such as cooperative behavior and hierarchical clustering. The heterogeneity of the interaction network is held responsible for the observed promotion of cooperation. We hope our work may offer an explanation for the origin of large-scale cooperative behavior among unrelated individuals.     

An evolutionary game theory model of binary opinion formation

A basic characteristic of most opinion models is that people tend to agree or compromise in the opinion interaction, which could be hopefully described by cooperative games in the evolutionary game theory framework. This paper presents game theory methods to model the formation of binary opinions: cooperative games are proposed to model the interaction rules of general people who tend to find an agreement; minority games are proposed to model the behaviors of contrarians; opinion preference is considered by varying the payoff values. The Majority Voter model could be restored from the proposed games. The game theory models show evolutionary results similar to traditional opinion models. Specially, the evolution of opinions with consideration of contrarians is in accordance with the Galam model. Furthermore, influences of evolving rule, network topology and initial distribution of opinions are studied through numerical simulations. Discussions about methods to promote or hinder the consensus state at the best equilibrium point are given.     

Optional contributions have positive effects for volunteering public goods games

Public goods (PG) games with the volunteering mechanism are referred to as volunteering public goods (VPG) games, in which loners are introduced to the PG games, and a loner obtains a constant payoff but not participating the game. Considering that small contributions may have positive effects to encourage more players with bounded rationality to contribute, this paper introduces optional contributions (high value or low value) to these typical VPG games—a cooperator can contribute a high or low payoff to the public pools. With the low contribution, the logit dynamics show that cooperation can be promoted in a well mixed population comparing to the typical VPG games, furthermore, as the multiplication factor is greater than a threshold, the average payoff of the population is also enhanced. In spatial VPG games, we introduce a new adjusting mechanism that is an approximation to best response. Some results in agreement with the prediction of the logit dynamics are found. These simulation results reveal that for VPG games the option of low contributions may be a better method to stimulate the growth of cooperation frequency and the average payoff of the population.     

Promotion of cooperation induced by nonuniform payoff allocation in spatial public goods game

A nonuniform payoff allocation mechanism is proposed for spatial public goods games where individuals are nodes on a scale-free network. Each individual is assigned a weight k_i ^α, where k_i is the degree of individual i and α is an adjustable parameter that controls the degree of diversity in individuals’ profits. During the evolution progress, the allocation of payoff on individual i is assumed to be proportional to its weight. Individuals synchronously update their strategies according to the stochastic rule with a fixed noise level. It is found that there exists an optimal value of α which yields the highest level of cooperation. Other pertinent quantities, including the payoff and the probability of finding a node playing as cooperator versus the degree, are also investigated computationally and analytically. Our results suggest that a suitable degree of diversity among individuals can promote the emergence of cooperation.     

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.     

Cooperation and charity in spatial public goods game under different strategy update rules

Human cooperation can be influenced by other human behaviors and recent years have witnessed the flourishing of studying the coevolution of cooperation and punishment, yet the common behavior of charity is seldom considered in game-theoretical models. In this article, we investigate the coevolution of altruistic cooperation and egalitarian charity in spatial public goods game, by considering charity as the behavior of reducing inter-individual payoff differences. Our model is that, in each generation of the evolution, individuals play games first and accumulate payoff benefits, and then each egalitarian makes a charity donation by payoff transfer in its neighborhood. To study the individual-level evolutionary dynamics, we adopt different strategy update rules and investigate their effects on charity and cooperation. These rules can be classified into two global rules: random selection rule in which individuals randomly update strategies, and threshold selection rule where only those with payoffs below a threshold update strategies. Simulation results show that random selection enhances the cooperation level, while threshold selection lowers the threshold of the multiplication factor to maintain cooperation. When charity is considered, it is incapable in promoting cooperation under random selection, whereas it promotes cooperation under threshold selection. Interestingly, the evolution of charity strongly depends on the dispersion of payoff acquisitions of the population, which agrees with previous results. Our work may shed light on understanding human egalitarianism.     

Efficiency based strategy spreading in the prisoner’s dilemma game

In contrast to well-mixed populations, discrete interaction patterns have been shown to support cooperation in the prisoner’s dilemma game, and a scale-free network topology may even lead to a dominance of cooperation over defection. The majority of studies assumes a strategy adoption scheme based on accumulated payoffs. The use of accumulated payoffs, however, is incompatible with the integral property of the underlying replicator dynamics to be invariant under a positive affine transformation of the payoff function. We show that using instead the payoff per interaction to determine the strategy spread, which has been suggested recently and recovers the required invariance, results in fundamentally different dynamical behavior under a synchronized strategy adoption considered here. Most notably, in such an efficiency based scenario the advantage of a scale-free network topology vanishes almost completely. We present a detailed explanation of the fundamentally altered dynamical behavior.     

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.     

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.