Evolutionary game dynamics of combining two different aspiration-driven update rules in structured populations

In evolutionary games,most studies on finite populations have focused on a single updating mechanism.However,given the differences in individual cognition,individuals may change their strategies according to different updating mechanisms.For this reason,we consider two different aspiration-driven updating mechanisms in structured populations:satisfied-stay unsatisfied shift(SSUS)and satisfied-cooperate unsatisfied defect(SCUD).To simulate the game player’s learning process,this paper improves the particle swarm optimization algorithm,which will be used to simulate the game player’s strategy selection,i.e.,population particle swarm optimization(PPSO)algorithms.We find that in the prisoner’s dilemma,the conditions that SSUS facilitates the evolution of cooperation do not enable cooperation to emerge.In contrast,SCUD conditions that promote the evolution of cooperation enable cooperation to emerge.In addition,the invasion of SCUD individuals helps promote cooperation among SSUS individuals.Simulated by the PPSO algorithm,the theoretical approximation results are found to be consistent with the trend of change in the simulation results.

Stochastic evolutionary public goods game with first and second order costly punishments in finite populations

We study the stochastic evolutionary public goods game with punishment in a finite size population. Two kinds of costly punishments are considered, i.e., first-order punishment in which only the defectors are punished, and second-order punishment in which both the defectors and the cooperators who do not punish the defective behaviors are punished. We focus on the stochastic stable equilibrium of the system. In the population, the evolutionary process of strategies is described as a finite state Markov process. The evolutionary equilibrium of the system and its stochastic stability are analyzed by the limit distribution of the Markov process. By numerical experiments, our findings are as follows.（i） The first-order costly punishment can change the evolutionary dynamics and equilibrium of the public goods game, and it can promote cooperation only when both the intensity of punishment and the return on investment parameters are large enough.（ii）Under the first-order punishment, the further imposition of the second-order punishment cannot change the evolutionary dynamics of the system dramatically, but can only change the probability of the system to select the equilibrium points in the ＂C＋P＂ states, which refer to the co-existence states of cooperation and punishment. The second-order punishment has limited roles in promoting cooperation, except for some critical combinations of parameters.（iii） When the system chooses＂C＋P＂ states with probability one, the increase of the punishment probability under second-order punishment will further increase the proportion of the ＂P＂ strategy in the ＂C＋P＂ states.

Some Analytical Properties of the Model for Stochastic Evolutionary Games in Finite Populations with Non-uniform Interaction Rate

Traditional evolutionary games assume uniform interaction rate, which means that the rate at which individuals meet and interact is independent of their strategies. But in some systems, especially biological systems, the players interact with each other discriminately. Taylor and Nowak (2006) were the first to establish the corresponding non-uniform interaction rate model by allowing the interaction rates to depend on strategies. Their model is based on replicator dynamics which assumes an infinite size population. But in reality, the number of individuals in the population is always finite, and there will be some random interference in the individuals' strategy selection process. Therefore, it is more practical to establish the corresponding stochastic evolutionary model in finite populations. In fact, the analysis of evolutionary games in a finite size population is more difficult. Just as Taylor and Nowak said in the outlook section of their paper, 'The analysis of non-uniform interaction rates should be extended to stochastic game dynamics of finite populations.' In this paper, we are exactly doing this work. We extend Taylor and Nowak's model from infinite to finite case, especially focusing on the influence of non-uniform connection characteristics on the evolutionary stable state of the system. We model the strategy evolutionary process of the population by a continuous ergodic Markov process. Based on the limit distribution of the process, we can give the evolutionary stable state of the system. We make a complete classification of the symmetric 2×2 games. For each case game, the corresponding limit distribution of the Markov-based process is given when noise intensity is small enough. In contrast with most literatures in evolutionary games using the simulation method, all our results obtained are analytical. Especially, in the dominant-case game, coexistence of the two strategies may become evolutionary stable states in our model. This result can be used to explain the emergence of cooperation in the Prisoner is Dilemma Games to some extent. Some specific examples are given to illustrate our results.

Game Modeling Research for Urbanization and Epidemic Control

To aid in the sustainable development of cities this paper examines methods for urbanization and epidemic control. Using, as a foundation, game theory from modern control theory, a set of strategies for modeling urbanization and epidemic control are examined by analyzing and studying the current condition of China including its population, economy, resources and city management methods. Urbanization and epidemic control solving strategies are probed and the solution to a simulated example is provided. The conclusion from this research is that the speed of Chinese urbanization should be slowed to match the condition of resources and level of city management available.

The Generic Uniqueness and Well-Posedness of NashEquilibria for Stable Population Games

This paper aims at studying a new kind of stable population games introduced by J.Hofbauer and H.Sandholm in 2009.We first construct a complete distance space M consisting of stable population games and show that most of stable population games have unique Nash equilibrium point that according to Baire’s category theorem.It implies that every stable population game that possesses more than one Nash equilibrium can be approached arbitrarily by a sequence of the stable population game each of which has a unique Nash equilibrium.Then,we construct a bounded rationality function and deduce some results on the generic well-posedness implying Tikhonov well-posedness and Hadamard well-posedness for stable population games.

AN INVARIANCE PRINCIPLE IN LARGE POPULATION STOCHASTIC DYNAMIC GAMES

We study large population stochastic dynamic games where the so-called Nash certainty equivalence based control laws are implemented by the individual players. We first show a martingale property for the limiting control problem of a single agent and then perform averaging across the population; this procedure leads to a constant value for the martingale which shows an invariance property of the population behavior induced by the Nash strategies.

Linear Quadratic Leader-Follower Stochastic Differential Games:Closed-Loop Solvability

In this paper,a leader-follower stochastic differential game is studied for a linear stochastic differential equation with quadratic cost functionals.The coefficients in the state equation and the weighting matrices in the cost functionals are all deterministic.Closed-loop strategies are introduced,which require to be independent of initial states;and such a nature makes it very useful and convenient in applications.The follower first solves a stochastic linear quadratic optimal control problem,and his optimal closed-loop strategy is characterized by a Riccati equation,together with an adapted solution to a linear backward stochastic differential equation.Then the leader turns to solve a stochastic linear quadratic optimal control problem of a forward-backward stochastic differential equation,necessary conditions for the existence of the optimal closed-loop strategy for the leader is given by a Riccati equation.Some examples are also given.

航天器姿态控制群体博弈分布式分配方法

针对由多个细胞星构成的组合卫星的姿态控制问题,提出了一种包含控制力矩计算层与冗余力矩分配层的双层姿态控制方法。将细胞星间的冗余力矩分配问题转化为群体博弈的策略选择问题,综合考虑能量消耗、飞轮输出力矩裕度和飞轮角动量裕度设计收益函数,以力矩分配系数作为群体质量,以细胞星作为策略建立群体博弈模型。考虑群体演化中模仿和比较形成的不同演化策略,分别采用Smith动力学以及复制器动力学修订协议求解博弈的Nash均衡解,并利用有限制策略的群体博弈理论形成分布式冗余力矩分配方式,得到各个细胞星的控制策略。最后通过仿真实验验证了此分配方式的有效性。

群体博弈理论的新进展

群体博弈理论是近三十年来发展起来的博弈论的新方向,源于1950年J.Nash在其博士学位论文中关于有限非合作博弈混合策略和平衡点的“Mass-Action”解释,建立了由众多个体组成的群体及社会中,个体的理性决策行为理论,在社会学、生物学、经济学、管理学、信息科学等领域有广泛和深入的应用。本文介绍近年来群体博弈理论的研究成果及新进展,探讨群体博弈理论的发展动向。

Population Genomic Analysis and De Novo Assembly Reveal the Origin of Weedy Rice as an Evolutionary Game

Crop weediness,especially that of weedy rice(Oryza sativa f.spontanea),remains mysterious.Weedy rice possesses robust ecological adaptability;however,how this strain originated and gradually formed proprietary genetic features remains unclear?Here,we demonstrate that weedy rice at Asian high latitudes(WRAH)is phylogenetically well defined and possesses unselected genomic characteristics in many divergence regions between weedy and cultivated rice.We also identified novel quantitative trait loci underlying weedy-specific traits,and revealed that a genome block on the end of chromosome 1 is associated with rice weediness.To identify the genomic modifications underlying weedy rice evolution,we generated the first de novo assembly of a high-quality weedy rice genome(WR04-6),and conducted a comparative genomics study between WR04-6 with other rice reference genomes.Multiple lines of evidence,including the results of demographic scenario comparisons,suggest that differentiation between weedy rice and cultivated rice was initiated by genetic improvement of cultivated rice and that the essence of weediness arose through semi-domestication.A plant height model further implied that the origin of WRAH can be modeled as an evolutionary game and indicated that strategy-based selection driven by fitness shaped its genomic diversity.

基于全基因组SNPs标记对河南斗鸡遗传多样性及选择信号分析

【目的】对河南斗鸡品种的遗传多样性与全基因组选择信号进行分析,挖掘河南斗鸡品种重要的种质特性基因。【方法】使用AffymetrixAxiom 600K高密度鸡基因分型芯片对来自9个品种的173只鸡的群体(包括20只河南斗鸡及153只商品鸡)进行基因分型;计算各个品种的期望杂合度、观测杂合度、次等位基因频率及核苷酸多样性评估地方鸡群体的遗传多样性;通过构建系统发育树、主成分分析、祖先成分分析方法研究品种的群体结构;利用斗鸡与商品鸡的成对遗传分化指数值进行选择信号分析。【结果】河南斗鸡及各商品鸡群体的观测杂合度为0.153~0.311,期望杂合度为0.158~0.315,次等位基因频率为0.111~0.234,核苷酸多样性为9.77×10^(-5)~1.56×10^(-4),且斗鸡的遗传多样性低于商品肉鸡品种,高于商品蛋鸡品种。系统发育树、主成分分析及祖先成分分析表明品种间有明显的群体分化。河南斗鸡与商品鸡群的主成分分析发现,河南斗鸡与商品肉鸡品种的遗传距离相对较近;将河南斗鸡和商品鸡群进行遗传选择信号后分析发现,河南斗鸡在神经,骨骼肌肉发育,免疫等性状经过高度选择。【结论】本研究从全基因组水平探究了河南斗鸡的遗传多样性和群体结构,筛选出候选基因,为河南斗鸡遗传资源保护和利用提供参考。

城市基层社区人口属地治理的实践逻辑——基于J市城中村社区双重治理的考察

我国城市治理逐步走向精细化,属地化治理理念已在基层社区得到落实。基于对J市城中村社区典型个案考察,发现常态化时期与紧急性时期存在双重治理模式。流动人口个人信息收集的路径依赖,使户籍地与居住地出现保护层面的城乡错位;流动人口居住空间属性的法律迷思,催生出居委会、村委会与开发商之间责任层面的村居博弈。错位的实质在于人户分离的属地治理模式并未完全转向实时动态的属地治理模式;博弈的实质在于分散流动人口社会服务的供给责任,以回避常态化实践与紧急性动员之间存在的资源配置真空。在双重治理中,户籍制度、产权制度是治理困境的驱动机制,资源局限、服务不足是治理不善的内在逻辑。本研究有助于理解城中村社区人口属地化治理困境的制度根源,并提升和优化基层社会治理。

异构无线网络用户网络关联优化:一种基于群体博弈的方法

针对异构无线网络(Heterogeneous Wireless Networks,HWNs)负载平衡问题,提出了一种基于群体博弈的用户网络关联方案.首先将HWNs系统用户网络关联问题抽象成一个群体博弈模型,根据用户在网络中得到的收益函数,证明该群体博弈满足势博弈的条件.利用复制动态作为演化动态工具,证明演化的结果最终会收敛到纳什均衡,这个特性确保了每个用户关联到一个效用最优的网络.然后证明纳什均衡点能最大化整个HWNs系统的吞吐量,保证了纳什均衡的有效性.最后,基于复制动态原理提出了用户网络关联算法.仿真实验模拟了用户网络选择过程,得到了均衡点,验证了理论分析的结果.

复杂网络上的演化博弈

主要介绍了近年来复杂网络上的演化博弈研究现状和研究方向.复杂网络理论的发展为描述博弈关系提供了系统且方便的框架,网络上的节点表示博弈个体,边代表与其邻居的博弈关系.介绍了经典演化博弈论中的演化稳定策略概念和复制动力学方程,以及二者的相互联系.介绍了混合均匀有限人口中随机演化动力学问题,并给出了与确定复制方程的相互转化关系.介绍了小世界、无标度等复杂网络上演化博弈的研究结论,给出了复杂网络上演化博弈论的未来发展方向.

群体性突发事件产生根源的主观博弈分析

本文运用主观博弈模型分析了我国群体性突发事件的产生根源。社会弱势群体考虑对收入差距敏感程度这一私人信息后,其行动策略集合发生变化,运用前向归纳法对弱势群体采取非子博弈纳什均衡的斗争策略具体条件进行了分析。结果表明,群体性突发事件的产生条件取决于弱势群体对博弈收益差距敏感程度、自身收益的变化率和现存社会体制下各社会阶层采取不同策略的预期收益等因素。

创新型产品供应网络运营最优控制与清晰联盟博弈协调

研究某创新型产品在市场需求随机波动下的运输与库存最优控制策略和多节点库存运输的网络协调。首先以布朗运动描述市场随机累计需求,在满足高服务水平(保证无缺货)的同时考虑常规和紧急两种运输方式及库存补货策略,证明和求解出该产品的单节点和多节点最优库存瞬时控制策略,使得系统长期平均运营成本最小化。采用数值分析和仿真揭示了最优控制策略下单分销商和多分销商系统的运营绩效与各参数之间的变化趋势和敏感性,发现多分销商集中决策相对于分散决策不一定能带来更低的运营成本。以清晰联盟博弈刻画和证明了在补货流和需求流平衡时多分销商分散决策演化为集中运营联合控制后能更有效地协调供应链、降低运营成本,分别证明求解了单产品和多产品情况下清晰联盟博弈核的存在性及其条件,最后给出比例法则和扩充Shapley值两种总体单调分配方案作为该清晰联盟博弈成本分摊的合理预测,并解释了两者差异性的来源。

延边地区人口回流的演化博弈分析及策略研究

近年延边地区出现持续性人口外流现象,已导致人口负增长、人口红利消失、经济增长能力受限等问题。本文利用演化博弈方法分析延边地区人口回流与政府回流措施的策略选择,研究结果表明,延边地区发展多元化农业与实施劳动技能培训、推进产业结构升级与完善资源配置效率、发展物流服务与构建产业网络以及加快城镇化建设与推动区域发展等策略建议将有助于延边地区人口回流,推动延边地区经济发展。

基于Parrondo悖论博弈的生物系统中合作进化研究

从生物进化理论的两个基础即生存竞争和适者生存出发,提出在个体生存和进化过程中存在两种博弈关系:个体之间的零和博弈及个体与自然之间的负博弈,设计一种Parrondo悖论博弈游戏以模拟生物种群中个体的生存模式,研究个体间合作的产生和发展。结果表明:合作是个体对自然选择的一种适应性,合作小群体中的个体相对于种群中其它不合作的个体,具有生存优势;个体合作产生的另一积极效果是使种群在与自然的博弈中获得正收益,一个种群中合作的个体越多,这个种群越具有生存优势-完全由自私个体组成的种群将被自然淘汰;保守合作策略具有良好的初始成活性,可通过小群体的方式有效侵入不合作的种群,同时还具有稳定性,不合作的小群体不能有效侵入保守合作的种群;以家庭、家族等为单位的小群体构成的生物种群,各个小群体内部合作,小群体之间竞争,这种构成方式不仅利于小群体中的个体生存,也推动了整个种群的生存繁衍,这个结论与绝大多数生物系统的观察资料一致。

区域人口、资源与环境公平性问题的博弈分析

在经济社会活动中 ,由于人口、资源与环境的非公平分配引发了区域内的矛盾与冲突 ,从而制约了区域可持续发展。如何化解区域的矛盾与冲突 ,实现人口、资源与环境的公平性 ,本文试图以博弈论来研究这一问题。首先本文对区域内代际公共资源与环境公平性作博弈分析 ,揭示了若没有制度安排与约束 ,区域内非公平性、非协调性是普遍存在的现象。其次本文对区域内公共资源与环境公平性作博弈分析 ,揭示了代内公共资源与环境利用的非公平性。最后本文研究了公共资源公平利用的制度安排及其激励问题。

我国群众体育的现状及其发展策略

从体育人口、参与体育锻炼的意识及体育消费观念等方面论过了我国群众体育的现状。认为要培养高素质群众体育指导队伍,大力宣传强身健体的理念,动员社会各方面的力量支持群众体育,组织全民参与体育。特别强调要充分发掘我国的民族体育资源为群众体育服务。