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.     

降雪干扰下基于演化博弈的低轨量子卫星多用户切换策略

低轨道量子卫星是构建全球天地一体化量子保密通信网的重要组成部分。单颗低轨量子卫星服务时间有限,为了保证卫星与地面用户之间的持续通信,地面终端需要及时切换至其他可供服务的卫星。为了解决降雪环境干扰下地面多用户量子卫星切换场景下的阈值判决问题,分析了大气雪环境对量子星地链路的衰减影响,提出了一种基于演化博弈的多属性量子卫星切换策略。根据用户的带宽、卫星剩余服务时间及链路衰减三个属性定义效用函数,根据星间传输时延、信道纠缠度定义开销函数,最终得到用户的收益函数,建立演化博弈切换模型。仿真结果表明,该策略具有稳定性和公平性,能够有效均衡卫星的负载,且与基于最低链路衰减和最优纠缠度的单属性切换策略相比,切换成功率分别提升了1.2%和1.5%,这对未来降雪干扰环境下低轨量子卫星网络的多用户动态切换有一定的参考意义。     

基于遗传算法的重复囚徒困境博弈策略在复杂网络中的演化

利用遗传算法研究重复囚徒困境博弈策略在复杂网络中的演化.研究结果表明：处于复杂网络中有记忆的个体通过基因的复制、重组、变异和选择能够进化出一种自组织的合作机制.这种合作机制既能够在群体中激发合作行为的产生，加强和维护持续的合作行为，同时又能对背叛的个体进行惩罚和报复，因此能够促使复杂网络中进化出具有很高合作率的群体. 关键词： 复杂网络 遗传算法 进化博弈 合作     

瞬态液晶技术在涡轮叶片内部冷却研究中的应用

瞬态液晶测量技术能有效测量物体表面的换热系数,目前已经在传热研究中得到了广泛的应用。本文重点介绍了该测量方法在高温涡轮叶片内部冷却传热研究中的实验过程及应用。对内部冷却U型通道的传热研究表明:气膜抽吸作用下,通道内孔附近的传热得到强化,但区域平均传热系数变化不大;同时抽吸能使带肋通道中的压力损失有所降低。为了满足叶片冷却设计中对传热和压力损失的不同要求,改变弯头区的结构形式是一种有效的手段。实验结果进一步表明,瞬态液晶测量方法能准确地测量内部冷却通道中的传热分布,能为测量和优化涡轮叶片内部冷却传热特性提供可靠的数据支持。     

CAI在高中物理教学中的应用策略

论述了ＣＡＩ软件的设计原则,根据实践阐述了“人一机”交互探讨式教学、演示程序、模拟工具程序和实践的辅助手段等方式在物理教学中的应用策略．     

零延时RS485模块在列车车载防火检测系统中的应用研究

随着高速列车技术的飞跃发展,车载设备之间的通讯信息、列车的故障检测和诊断信息、车内视频监控信息等信息数据的剧增,对信息承载媒介和通讯接口设备在可靠性和实时性方面提出了更高的要求;通过对RS485模块的研究设计了一种零延时RS485模块,应用于以太网主从式结构的列车车载防火检测系统中,达到实时、高效、安全可靠的设计目的;使用Multisim软件对零延时电路进行仿真验证,结果表明该设计的零延时RS485模块具有可靠的实时性。     

分层教学在中考物理复习中的实施策略

本文阐述了中考物理复习中实施分层教学的优越性和必要性,并从目标分层、教学内容分层、作业分层、评价分层四个维度陈述分层教学在中考物理复习中的实施策略.     

思维定势在物理学习中的负面影响及其应对策略

通过具体实例分析了思维定势在高中物理学习中的负面影响,并分别从三个方面提出了应对策略。     

部分相干圆刃型位错光束在生物组织中的动态演化

以广义惠更斯-菲涅耳原理为基础,利用推导的部分相干圆刃型位错光束在小鼠真皮组织传输中的交叉谱密度函数解析表达式,研究了光束初始参量(光束波长λ和圆刃型位错数目n)和传输距离z对光束归一化光强分布、相位演化和传输轨迹的影响.结果表明,位错数为n的部分相干圆刃型位错光束,源平面内中心光强最大,两侧对称分布着2n个次峰.随传...     

子孔径拼接技术在大口径高陡度非球面检测中的应用

为了能够精确地完成对大口径高陡度非球面在细磨和抛光过程中的测量,提出了一种将子孔径拼接技术和补偿技术相结合的检测方法。介绍了该方法的基本原理,建立了合理的数学模型,编制了拼接计算软件。利用该方法对一外形尺寸为400 mm×300 mm的高次离轴非球面进行了测试,通过最小二乘法拟合消去各子孔径相对基准子孔径的调整误差以及整个系统的装调定位误差,得到了准确的全孔径面形分布。对实验精度和误差来源进行了分析,并将拼接面形与全孔径测量面形相对比,二者是一致的。     

Evolutionary snowdrift game with disordered environments in mobile societies

We investigate an evolutionary snowdrift game on a square $N=L\times L$ lattice with periodic boundary conditions, where a population of $n_{0}$ ($n_{0}\leq N$) players located on the sites of this lattice can either cooperate with or defect from their nearest neighbours. After each generation, every player moves with a certain probability $p$ to one of the player's nearest empty sites. It is shown that, when $p=0$, the cooperative behaviour can be enhanced in disordered structures. When $p>0$, the effect of mobility on cooperation remarkably depends on the payoff parameter $r$ and the density of individuals $\rho$ ($\rho=n_{0}/N$). Compared with the results of $p=0$, for small $r$, the persistence of cooperation is enhanced at not too small values of $\rho$; whereas for large $r$, the introduction of mobility inhibits the emergence of cooperation at any $\rho<1$; for the intermediate value of $r$, the cooperative behaviour is sometimes enhanced and sometimes inhibited, depending on the values of $p$ and $\rho$. In particular, the cooperator density can reach its maximum when the values of $p$ and $\rho$ reach their respective optimal values. In addition, two absorbing states of all cooperators and all defectors can emerge respectively for small and large $r$ in the case of $p>0$.     

Evolution of cooperation in the snowdrift game among mobile players with random-pairing and reinforcement learning

The evolutionary spatial game in a mobile population has attracted many researchers of biological, social and economic sciences. Considering some facts observed in the real world, this paper proposes a novel spatial evolutionary snowdrift game model with movable players. In this model, one player interacts only with the nearest neighbor in each turn, and makes decision in a reinforcement learning way. In a very large range of the parameters moving ability enhances cooperation, but under some special condition, velocity heavily depresses cooperation. Some explanations have also been given out by investigating the strategy-change behavior of players. The findings may be helpful in understanding cooperative behavior in natural and social systems consisting of mobile agents.     

Zero-determinant strategy:An underway revolution in game theory

Repeated games describe situations where players interact with each other in a dynamic pattern and make decisions according to outcomes of previous stage games. Very recently, Press and Dyson have revealed a new class of zero-determinant(ZD) strategies for the repeated games, which can enforce a fixed linear relationship between expected payoffs of two players, indicating that a smart player can control her unwitting co-player’s payoff in a unilateral way [Proc. Acad. Natl. Sci.USA 109, 10409(2012)]. The theory of ZD strategies provides a novel viewpoint to depict interactions among players,and fundamentally changes the research paradigm of game theory. In this brief survey, we first introduce the mathematical framework of ZD strategies, and review the properties and constrains of two specifications of ZD strategies, called pinning strategies and extortion strategies. Then we review some representative research progresses, including robustness analysis,cooperative ZD strategy analysis, and evolutionary stability analysis. Finally, we discuss some significant extensions to ZD strategies, including the multi-player ZD strategies, and ZD strategies under noise. Challenges in related research fields are also listed.     

Evolutionary snowdrift game on heterogeneous Newman--Watts small-world network

We study the evolutionary snowdrift game in a heterogeneous Newman-Watts small-world network. The heterogeneity of the network is controlled by the number of hubs. It is found that the moderate heterogeneity of the network can promote the cooperation best. Besides, we study how the hubs affect the evolution of cooperative behaviours of the heterogeneous Newman-Watts small-world network. Simulation results show that both the initial states of hubs and the connections between hubs can play an important role. Our work gives a further insight into the effect of hubs on the heterogeneous networks.     

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.     

Costly punishment and cooperation in the evolutionary snowdrift game

The role of punishments in promoting cooperation is an important issue. We incorporate costly punishments into the snowdrift game (SG) by introducing a third punishing (P) character, and study the effects. The punishers, who carry basically a cooperative (C) character, are willing to pay a cost α so as to punish a non-cooperative (D) opponent by β. Depending on the initial fractions of the characters, α, β, and the cost-to-benefit ratio r in the SG, the three-character system evolves into a steady state consisting either only of C and P characters or only of C and D characters, in a well-mixed population. The former situation represents an enhancement in cooperation relative to the SG, while the latter is similar to the SG. The dynamics in approaching these different steady states are found to be different. Analytically, the key features in the dynamics and the steady states observed in simulations are captured by a set of differential equations. The sensitivity to the initial distribution of characters is studied by depicting the flow in a phase portrait and analyzing the nature of fixed points. The analysis also shows the role of P-character agents in preventing a system from invasion by D-character agents. Starting from a population consisting only of C and P agents, a D-character agent intended to invade the system cannot survive when the initial fraction of P agents is greater than r/β. Our model, defined intentionally as a simulation algorithm, can be readily generalized to incorporate many interesting effects, such as those in a networked population.     

Evolutionary snowdrift game incorporating costly punishment in structured populations

The role of punishment and the effects of a structured population in promoting cooperation are important issues. Within a recent model of snowdrift game (SG) incorporating a costly punishing strategy (P), we study the effects of a population connected through a square lattice. The punishers, who carry basically a cooperative (C) character, are willing to pay a cost α$\alpha$ so as to punish a non-cooperative (D) opponent by β$\beta$. Depending on α$\alpha$, β$\beta$, the cost-to-benefit ratio r$r$ in SG, and the initial conditions, the system evolves into different phases that could be homogeneous or inhomogeneous. The spatial structure imposes geometrical constraint on how one agent is affected by neighboring agents. Results of extensive numerical simulations, both for the steady state and the dynamics, are presented. Possible phases are identified and discussed, and isolated phases in the r–β$r\text{–}\beta$ space are identified as special local structures of strategies that are stable due to the lattice structure. In contrast to a well-mixed population where punishers are suppressed due to the cost of punishment, the altruistic punishing strategy can flourish and prevail for appropriate values of the parameters, implying an enhancement in cooperation by imposing punishments in a structured population. The system could evolve to a phase corresponding to the coexistence of C, D, and P strategies at some particular payoff parameters, and such a phase is absent in a well-mixed population. The pair approximation, a commonly used analytic approach, is extended from a two-strategy system to a three-strategy system. We show that the pair approximation can, at best, capture the numerical results only qualitatively. Due to the improper way of including spatial correlation imposed by the lattice structure, the approximation does not give the frequencies of C, D, and P accurately and fails to give the homogeneous AllD and AllP phases.     

Evacuation of pedestrians from a hall by game strategy update

In this paper, a cellular automaton model considering game strategy update is proposed to study the pedestrian evacuation in a hall. Pedestrians are classified into two categories, i.e., cooperators and defectors, and they walk to an exit according to their own strategy change. The conflicts that two or three pedestrians try to occupy the same site at the same time are investigated in the Game theory model. Based on it, the relationship between the pedestrian flow rate and the evacuation time as well as the variation of cooperative proportion against evacuation time is investigated from the different initial cooperative proportions under the influence of noise. The critical value of the noise is found when there is a small number of defectors in the initial time. Moreover, the influences of the initial cooperative proportion and strength of noise on evacuation are discussed. The results show that the lower the initial cooperative proportion as well as the bigger the strength of noise, the longer the time it takes for evacuation.     

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.     

Cooperative dynamics of snowdrift game on spatial distance-dependent small-world networks

We investigate the evolution of cooperative behaviors of small-world networking agents in a snowdrift game mode, where two agents (nodes) are connected with probability depending on their spatial Euclidean lattice distance in the power-law form controlled by an exponent α. Extensive numerical simulations indicate that the game dynamics crucially depends on the spatial topological structure of underlying networks with different values of the exponent α. Especially, in the distance-independent case of α=0, the small-world connectivity pattern contributes to an enhancement of cooperation compared with that in regular lattices, even for the case of having a high cost-to-benefit ratio r. However, with the increment of α>0, when r≥0.4, the spatial distance-dependent small-world (SDSW) structure tends to inhibit the evolution of cooperation in the snowdrift game.