合作进化模型综述

作者综述了合作进化模型的最新研究成果。合作进化模型以"囚徒困境"博弈模型为基础,为合作中的个体提供了一种与个体本身无关的策略优化机制,以此探讨合作策略能够稳定进化的条件。基于直接或间接互惠理论的合作进化模型验证了在小规模社会中建立声誉机制有助于实现稳定的互惠合作;互惠可以看做是对合作行为的奖赏,开放的社会网络有助于实现较大范围内的合作;对非合作行为实施惩罚有助于实现多人合作,在一定条件下,由非合作者实施惩罚时的合作进化相较于由合作者实施时更稳定;群组竞争有利于合作文化或制度的传播,但无法解释群组融合后的合作问题。     

惩罚机制对影响力不同群体合作行为演化的影响

在无标度网络中,研究惩罚机制对群体合作行为演化的影响.采用进化博弈论中重复囚徒困境博弈策略,考虑影响力的多样化,模拟分析在影响力同质和异质网络中分别引入惩罚策略对个体间合作关系的影响.仿真结果表明:在影响力同质网络中,惩罚机制会激励合作行为;在度小节点影响力大的网络中,惩罚机制也同样提高了群体合作率;而在度大节点影响力大的网络中,惩罚会使群体中策略分布趋于一个均衡状态.     

直接互惠下量子囚徒困境的演化稳定分析

为深入探讨直接互惠和量子纠缠如何影响合作的演化,运用演化博弈理论的方法建立了直接互惠下量子囚徒困境模型,计算博弈动态的均衡点并对均衡点进行稳定性分析,讨论直接互惠参数和纠缠对均衡点的影响。分析结果表明,当直接互惠参数、量子纠缠在不同条件下,合作策略和背叛策略为演化稳定策略,并且当纠缠大于临界值时直接互惠行为促进合作;纠缠小于临界值时直接互惠行为抑制合作。最后通过数值仿真验证了理论的正确性。     

虚拟学术群组用户跨学科科研合作行为研究——以科学网和Mendeley为例

基于TPB理论向度,归纳和提取虚拟学术群组用户跨学科科研合作行为的影响因素,并引入跨学科科研合作行为意愿在影响因素与行为之间的中介作用;根据自我结构理论,引入自我结构类型对影响因素的调节作用,构建虚拟学术群组用户跨学科科研合作行为研究模型,利用调查问卷收集科学网和Mendeley总共479份样本数据,通过PLS～SEM方法对研究模型展开分析验证。研究结果表明,感知有用性、利他动机、学科文化和资源可用性通过跨学科科研合作行为意愿的中介作用间接显著影响跨学科科研合作行为;自我价值和互惠受自我结构类型的调节,自立自我负向显著调节互惠与Mendenly用户跨学科科研合作行为意愿的关联性;依存自我负向显著调节自我价值与科学网用户跨学科科研合作行为意愿的关联性。探索虚拟学术群组用户跨学科科研合作行为的影响因素,有助于推进跨学科科研合作行为和提升科研用户知识共享效率。     

带成本性的背叛行动对间接互惠种群进化博弈的影响

间接互惠通过声誉起作用,是促进种群合作的重要方式之一。借助于声誉的二阶评估社会规范,在经典的种群捐助博弈中引入带成本性的背叛行动,寻求合作性进化稳定策略的条件并探讨其平均收益。研究发现,在3种合作性进化稳定策略中,对坏声誉接受者采取较小成本的背叛行动,其策略所产生的平均收益小于无成本沉默策略的平均收益,而高于成本较高的惩罚策略的平均收益。     

港口污水处理监督的演化仿真分析

为实现港口经济的可持续发展,促进绿色港口建设,针对港口污水处理问题,引入了政府及港口污水处理企业作为研究对象,分析了政府静态奖惩、动态奖励、动态惩罚、动态奖惩四种机制下,博弈双方策略的选择及其稳定性,并采用系统动力学工具进行仿真分析。研究结果表明,政府静态奖惩机制下,当政府奖励力度或者惩罚力度增大到一定程度时,双方稳定策略可达到最理想的纯策略状态;当政府实施动态奖励机制时,系统也会逐渐稳定于纯策略状态;由于纯策略状态并不是一种稳定的状态,所以在政府静态奖惩和动态奖励机制下,系统均不存在稳定的Nash均衡点;当政府实施动态惩罚和动态奖惩机制时,系统存在稳定的Nash均衡点,且政府实施动态奖惩比只实施动态惩罚机制更有效。     

众创空间中创新合作违约惩罚机制研究 ——基于随机演化博弈模型

基于随机演化博弈理论,建立众创空间创新合作的违约惩罚机制模型。分析了系统的稳定性,并通过数值模拟证实了均衡点的演化轨迹。结果表明:在违约惩罚机制中,违约金的数额决定了系统的演化方向。当违约金能够抵消欺骗策略带来的超额收益时,违约金惩罚机制将很好地抑制众创空间创新合作中的欺骗倾向,促进主体采取诚信策略,从而实现众创空间生态系统的稳定健康运行。     

合作演化与网络博弈实验研究进展

围绕合作的演化与涌现,本文基于两人囚徒困境和多人公共品博弈模型,重点介绍了近年来关于直接互惠和网络互惠的理论与实验研究进展.重复博弈为直接互惠的产生提供了必要条件.零行列式策略作为直接互惠中的一个新理论,近期被从理论与实验方面深入研究.零行列式策略是一种单步记忆策略,它可以单方面决定博弈双方的收益关系,这为探索人类决策行为规律提供了新工具.网络博弈实验研究发现,动态网络可以提升并维持人类的合作行为,而静态网络是否促进合作涌现尚存在争议.网络博弈实验有助于理解社会网络重要结构的形成机理与复杂系统中的行为涌现.     

合作进化的研究进展

阐述了合作的进化对于理解生物（包括人类自身）组织行为的重要性．合作的进化描述了生物行为策略的选择过程,互相剥夺还是互相合作．在理论模型中则取决于作用双方再次相遇的概率（即未来贴现）、环境噪声的大小、人口的结构特征、对策的发生机制等因素．较优的策略能在长期内获得较高的支付值,表征了个体对环境的适应性,体现了自然选择的结果．同时探讨了进化策略的稳定性,以及由Ｎｏｗａｋ 等引入的反映合作疆域之争的空间对策问题     

公众参与下交通基础设施公私合作项目风险分担再谈判演化博弈

通过构建公众参与下交通基础设施公私合作（publicprivate partnership,PPP）项目风险分担再谈判演化博弈模型,分析如何规避企业再谈判过程中的机会主义行为。结果表明：当企业采取非机会主义行为策略所获得的收益小于采取机会主义行为策略所获得的收益时,公众参与能促使企业采取非机会主义行为策略;在公众参与概率较低的情况下,规避企业机会主义行为的一种重要方式是提高政府对企业机会主义行为的惩罚力度;不同的公众监督水平对政府处罚力度的要求不一样,在公众监督意愿较低的情况下需要政府加大对企业的惩罚力度才能迫使企业转变机会主义行为。     

Evolution and maintenance of cooperation via inheritance of neighborhood relationship

Cooperative behaviors are ubiquitous in nature and human society. It is very important to understand the internal mechanism of emergence and maintenance of cooperation. As we know now, the offsprings inherit not only the phenotype but also the neighborhood relationship of their parents. Some recent research results show that the interactions among individuals facilitate survival of cooperation through network reciprocity of clustering cooperators. This paper aims at introducing an inheritance mechanism of neighborhood relationship to explore the evolution of cooperation. In detail, a mathematical model is proposed to characterize the evolutionary process with the above inheritance mechanism. Theoretical analysis and numerical simulations indicate that high-level cooperation can emerge and be maintained for a wide variety of cost-to-benefit ratios, even if mutation happens during the evolving process.     

Emergence of cooperation and evolutionary stability in finite populations

To explain the evolution of cooperation by natural selection has been a major goal of biologists since Darwin. Cooperators help others at a cost to themselves, while defectors receive the benefits of altruism without providing any help in return. The standard game dynamical formulation is the 'Prisoner's Dilemma', in which two players have a choice between cooperation and defection. In the repeated game, cooperators using direct reciprocity cannot be exploited by defectors, but it is unclear how such cooperators can arise in the first place. In general, defectors are stable against invasion by cooperators. This understanding is based on traditional concepts of evolutionary stability and dynamics in infinite populations. Here we study evolutionary game dynamics in finite populations. We show that a single cooperator using a strategy like 'tit-for-tat' can invade a population of defectors with a probability that corresponds to a net selective advantage. We specify the conditions required for natural selection to favour the emergence of cooperation and define evolutionary stability in finite populations.     

Human cooperation: second-order free-riding problem solved?

Panchanathan and Boyd describe a model of indirect reciprocity in which mutual aid among cooperators can promote large-scale human cooperation without succumbing to a second-order free-riding problem (whereby individuals receive but do not give aid). However, the model does not include second-order free riders as one of the possible behavioural types. Here I present a simplified version of their model to demonstrate how cooperation unravels if second-round defectors enter the population, and this shows that the free-riding problem remains unsolved.     

A simple rule for the evolution of cooperation on graphs and social networks

A fundamental aspect of all biological systems is cooperation. Cooperative interactions are required for many levels of biological organization ranging from single cells to groups of animals. Human society is based to a large extent on mechanisms that promote cooperation. It is well known that in unstructured populations, natural selection favours defectors over cooperators. There is much current interest, however, in studying evolutionary games in structured populations and on graphs. These efforts recognize the fact that who-meets-whom is not random, but determined by spatial relationships or social networks. Here we describe a surprisingly simple rule that is a good approximation for all graphs that we have analysed, including cycles, spatial lattices, random regular graphs, random graphs and scale-free networks: natural selection favours cooperation, if the benefit of the altruistic act, b, divided by the cost, c, exceeds the average number of neighbours, k, which means b/c > k. In this case, cooperation can evolve as a consequence of 'social viscosity' even in the absence of reputation effects or strategic complexity.     

Influence of strategy continuity on cooperation in spatial prisoner’s dilemma games with migrating players

The phenomenon of cooperation is prevalent in both nature and human society. In this paper a simulative model is developed to examine how the strategy continuity influences cooperation in the spatial prisoner’s games in which the players migrate through the success-driven migration mechanism. Numerical simulations illustrate that the strategy continuity promotes cooperation at a low rate of migration, while impeding cooperation when the migration rate is higher. The influence of strategy continuity is also dependent on the game types. Through a more dynamic analysis, the different effects of the strategy continuity at low and high rates of migration are explained by the formation, expansion, and extinction of the self-assembled clusters of “partial- cooperators” within the gaming population.     

Emergence of group cooperation in public goods game on regular small-world network

The regular small-world network, which contains the properties of small-world network and regular network, has recently received substantial attention and has been applied in researches on 2-person games. However, it is a common phenomenon that cooperation always appears as a group behavior. In order to investigate the mechanism of group cooperation, we propose an evolutionary multi-person game model on a regular small-world network based on public goods game theory. Then, to make a comparison of frequency of cooperation among different networks, we carry out simulations on three kinds of networks with the same configuration of average degree: the square lattice, regular small-world network and random regular network. The results of simulation show that the group cooperation will emerge among these three networks when the enhancement factor r exceeds a threshold. Furthermore, time required for full cooperation on regular small-world network is slightly longer than the other networks, which indicates that the compact interactions and random interactions will promote cooperation, while the longer-range links are the obstacles in the emergence of cooperation. In addition, the cooperation would be promoted further by enhancing the random interactions on regular small-world network.     

Volunteering leads to rock-paper-scissors dynamics in a public goods game

Collective efforts are a trademark of both insect and human societies. They are achieved through relatedness in the former and unknown mechanisms in the latter. The problem of achieving cooperation among non-kin has been described as the 'tragedy of the commons', prophesying the inescapable collapse of many human enterprises. In public goods experiments, initial cooperation usually drops quickly to almost zero. It can be maintained by the opportunity to punish defectors or the need to maintain good reputation. Both schemes require that defectors are identified. Theorists propose that a simple but effective mechanism operates under full anonymity. With optional participation in the public goods game, 'loners' (players who do not join the group), defectors and cooperators will coexist through rock-paper-scissors dynamics. Here we show experimentally that volunteering generates these dynamics in public goods games and that manipulating initial conditions can produce each predicted direction. If, by manipulating displayed decisions, it is pretended that defectors have the highest frequency, loners soon become most frequent, as do cooperators after loners and defectors after cooperators. On average, cooperation is perpetuated at a substantial level.     

Human behaviour: Egalitarian motive and altruistic punishment

Altruistic punishment is a behaviour in which individuals punish others at a cost to themselves in order to provide a public good. Fehr and G?chter present experimental evidence in humans indicating that negative emotions towards non-cooperators motivate punishment, which, in turn, provokes a high degree of cooperation. Using Fehr and G?chter's original data, we provide an alternative analysis of their experiment that suggests that egalitarian motives are more important than motives for punishing non-cooperative behaviour. This finding is consistent with evidence that humans may have an evolutionary incentive to punish the highest earners in order to promote equality, rather than cooperation.     

Behaviorial evolution: does similarity breed cooperation?

Reciprocity, whether direct or indirect, is thought to be the key to establishing cooperation among non-relatives. But Riolo et al. have presented a model in which cooperation is instead based on similarity: agents donate only when their partner's 'tag' lies within a 'tolerance' range around their own. Here we point out that their model requires individuals with identical tags to cooperate with each other, and show that cooperation tends to collapse when individuals bearing identical tags are given the option of not donating. We therefore question their mechanism for maintaining cooperation without reciprocity.     

农户环保合作的演化博弈分析

通过演化博弈理论分析农户环保博弈系统的演化过程与均衡状态, 首先建立复制者动态方程, 分析系统的演化稳定性; 然后讨论影响系统的随机因素, 在此基础上建立随机演化博弈模型, 分析系统的随机演化动态和随机稳定性。结果表明, 环保合作能否成为系统演化的结果, 取决于两方面: 1) 农户在考虑环保行为的成本、收益以及农户认为环保行为的正外部性给自身造成的损失后, 所得到的净收益; 2) 博弈过程的惯例。因此要促进制度向农户环保合作制度演进, 可以采取选择性激励措施, 增加采取环保行为农户的收益, 选择性激励措施的供给者承担制度变迁的主要成本; 同时建立行为重复机制, 使有记忆的博弈中环保合作成为唯一惯例, 行为重复机制的提供者承担制度变迁的主要成本。