基于名声机制的重复囚徒困境合作博弈分析

处于重复囚徒困境下的博弈者存在相互合作的可能性。在此基础之上,探讨了一类具有两种状态的名声机制,并发现其中只有3个马尔可夫策略是高效的强健完美纳什均衡。研究表明,跟好名声者合作和背叛坏名声者的策略是最具吸引力的一个策略,此合作可最终成功实现并且持续下去。     

基于囚徒困境策略的改进HK网络上的合作博弈

为模拟现实世界的合作行为,本文在HK网络模型基础上提出了一种具有高聚类幂律可调性质的新的网络模型,并分析了囚徒困境博弈在此网络上的演化。通过仿真实验,研究了该网络的高聚类特性对合作行为的影响。大量实验表明,网络的高聚类特性可以极大促进合作现象的涌现。同时研究也发现,随着诱惑参数的变大,合作水平也会随之下降,但幅度不大。总之,该演化博弈模型可以促进合作现象的涌现并抵御背叛策略的传播。     

惩罚因子在重复囚徒困境博弈中的研究

针对囚徒困境博弈中收益矩阵参数无法动态更新的问题,提出一个带惩罚因子的囚徒困境博弈模型。该模型中的个体可以根据自身的策略,动态修改收益矩阵中的参数,在每轮博弈之后个体根据邻居收益更新自己的策略。仿真结果表明,惩罚因子可以有效地促进合作策略的涌现,另外发现,合作策略的涌现不仅与惩罚因子有关,而且与网络个体的初始策略有关。当社团内部的个体采取相同策略,社团之间采取不同策略时,更有利于合作策略的涌现。最后,惩罚因子还可以提高参与者的平均收益。     

囚徒困境中贴标签控制的促合作设计

研究囚徒困境中促进合作演化的控制设计及控制下的合作演化路径问题.基于标签捐赠机制,设计对个体贴标签的规则,增加个体的认知能力,协助个体决策.建立反馈控制下的合作演化动态模型,分析贴标签控制促进合作演化的实现途径,论证容许控制上界与控制效果之间的一致性.通过基于合作识别和基于背叛识别两种控制的比较,得到两个结论.一是合作率较低时,基于背叛识别的控制更容易促进合作率提升,反之,基于合作识别的控制则更容易实现.二是这两种识别方式需要相同的博弈重复次数.仿真分析各参数和控制上界对控制律设计和合作演化轨迹的影响.     

空间博弈中基于信号传递的合作行为演化仿真

为了研究信号传递对合作行为演化的影响,利用Repast仿真软件建立合作行为演化模型,根据信号和策略将个体分为利他者、排外者、谄媚者和背叛者,研究信号对合作水平的影响及机制.仿真结果表明,信号是影响合作水平的重要因素,演化过程中发出相同信号的个体形成团簇,发出不同信号的个体相互制约,并且合作水平随着b值的增大而降低.与无...     

有限次重复囚徒博弈中的合作机制研究

模仿现实中人们的决策方式,提出类"触发策略"的策略思想,将原问题由双策略的多阶段博弈转换为多策略的一次性博弈,并建立起扩展的支付矩阵;然后运用进化博弈理论,将随机扰动引入复制子动态,从理论上说明有限次重复囚徒博弈之所以能够涌现合作是复制效应和变异效应共同作用的结果;最后通过建立多主体系统的仿真模型,进一步分析和验证了合作涌现的门限条件和稳定状态。     

基于演化博弈研究移动和噪声对合作的影响

针对规则格子上的节点的自私行为不能有效抑制的问题,提出一个结合个体移动和噪声因素的演化囚徒困境模型。该模型结合ALLC、ALLD、TFT和TF2T四种策略来分析个体移动和噪声两个因素分别和共同对演化博弈中合作行为的影响。模型中的博弈者根据收益差异,可以移动到比当前位置收益高的邻居域的空位置,并且在反复博弈过程学习、模仿,不断调整博弈策略,提高博弈所得,最后达到进化稳定状态。最后在Matlab平台上进行仿真实验,实验结果表明,该模型能够促使个体合作,并且对个体的欺骗行为具有抑制作用。     

复杂网络上重复囚徒困境博弈的研究*

为了研究博弈理论在复杂网络上的影响,对Zachary网络应用重复囚徒困境博弈的思想提出了两种网络演化算法,即随机算法和伪度优先算法,并对重复博弈后的复杂网络特性进行了分析,其中包括度分布特性和聚集系数。最后采用Newman算法,对经过伪度优先算法后的网络进行社团结构分析,发现伪度优先算法可以明显改善网络的社团结构。结果表明经过两种算法后的网络,度分布依然服从幂律分布,聚集系数均有所增加,而且伪度优先算法增加幅度很大。     

Evolution of iterated prisoner's dilemma game strategies in structured demes under random pairing in game playing

We discuss the evolution of strategies in a spatial iterated prisoner's dilemma (IPD) game in which each player is located in a cell of a two-dimensional grid-world. Following the concept of structured demes, two neighborhood structures are used. One is for the interaction among players through the IPD game. A player in each cell plays against its neighbors defined by this neighborhood structure. The other is for mating strategies by genetic operations. A new strategy for a player is generated by genetic operations from a pair of parent strings, which are selected from its neighboring cells defined by the second neighborhood structure. After examining the effect of the two neighborhood structures on the evolution of cooperative behavior with standard pairing in game-playing, we introduce a random pairing scheme in which each player plays against a different randomly chosen neighbor at every round (i.e., every iteration) of the game. Through computer simulations, we demonstrate that small neighborhood structures facilitate the evolution of cooperative behavior under random pairing in game-playing.     

Cooperation mechanism in finite iterated prisoner's dilemma:revisit based on real-life decision making simulation

模仿现实中人们的决策方式,提出类“触发策略”的策略思想,将原问题由双策略的多阶段博弈转换为多策略的一次性博弈,并建立起扩展的支付矩阵;然后运用进化博弈理论,将随机扰动引入复制子动态,从理论上说明有限次重复囚徒博弈之所以能够涌现合作是复制效应和变异效应共同作用的结果;最后通过建立多主体系统的仿真模型,进一步分析和验证了合作涌现的门限条件和稳定状态.     

Crossover and evolutionary stability in the prisoner's dilemma

We examine the role played by crossover in a series of genetic algorithm-based evolutionary simulations of the iterated prisoner's dilemma. The simulations are characterized by extended periods of stability, during which evolutionarily meta-stable strategies remain more or less fixed in the population, interrupted by transient, unstable episodes triggered by the appearance of adaptively targeted predators. This leads to a global evolutionary pattern whereby the population shifts from one of a few evolutionarily metastable strategies to another to evade emerging predator strategies. While crossover is not particularly helpful in producing better average scores, it markedly enhances overall evolutionary stability. We show that crossover achieves this by (1) impeding the appearance and spread of targeted predator strategies during stable phases, and (2) greatly reducing the duration of unstable epochs, presumably by efficient recombination of building blocks to rediscover prior metastable strategies. We also speculate that during stable phases, crossover's operation on the persistently heterogeneous gene pool enhances the survival of useful building blocks, thus sustaining long-range temporal correlations in the evolving population. Empirical support for this conjecture is found in the extended tails of probability distribution functions for stable phase lifetimes.     

A voter model of the spatial prisoner's dilemma

The prisoner's dilemma (PD) involves contests between two players and may naturally be played on a spatial grid using voter model rules. In the model of spatial PD discussed here, the sites of a two-dimensional lattice are occupied by strategies. At each time step, a site is chosen to play a PD game with one of its neighbors. The strategy of the chosen site then invades its neighbor with a probability that is proportional to the payoff from the game. Using results from the analysis of voter models, it is shown that with simple linear strategies, this scenario results in the long-term survival of only one strategy. If three nonlinear strategies have a cyclic dominance relation between one another, then it is possible for relatively cooperative strategies to persist indefinitely. With the voter model dynamics, however, the average level of cooperation decreases with time if mutation of the strategies is included. Spatial effects are not in themselves sufficient to lead to the maintenance of cooperation     

Behavioral diversity, choices and noise in the iterated prisoner's dilemma

Real-world dilemmas rarely involve just two choices and perfect interactions without mistakes. In the iterated prisoner's dilemma (IPD) game, intermediate choices or mistakes (noise) have been introduced to extend its realism. This paper studies the IPD game with both noise and multiple levels of cooperation (intermediate choices) in a coevolutionary environment, where players can learn and adapt their strategies through an evolutionary algorithm. The impact of noise on the evolution of cooperation is first examined. It is shown that the coevolutionary models presented in this paper are robust against low noise (when mistakes occur with low probability). That is, low levels of noise have little impact on the evolution of cooperation. On the other hand, high noise (when mistakes occur with high probability) creates misunderstandings and discourages cooperation. However, the evolution of cooperation in the IPD with more choices in a coevolutionary learning setting also depends on behavioral diversity. This paper further investigates the issue of behavioral diversity in the coevolution of strategies for the IPD with more choices and noise. The evolution of cooperation is more difficult to achieve if a coevolutionary model with low behavioral diversity is used for IPD games with higher levels of noise. The coevolutionary model with high behavioral diversity in the population is more resistant to noise. It is shown that strategy representations can have a significant impact on the evolutionary outcomes because of different behavioral diversities that they generate. The results further show the importance of behavioral diversity in coevolutionary learning.     

协作式云资源博弈分配

针对用户对云资源的异构性需求和竞争问题,提出了一种协作式资源分配博弈策略。建立了资源分配的协作式博弈模型,定义了协作博弈的用户效用函数和评估函数,证明了在该效用函数下协作博弈存在唯一Nash均衡,并讨论了用户组建联盟对协作特征函数和整体效用的影响。实验结果表明,在该协作博弈策略下,个体用户通过组建联盟集体出价的方式,能够为联盟用户带来更大效用,以收敛方式实现Pareto改进。     

Role of cooperation in coupling game theory

A coupling game is a new model for partly cooperative and partly non-cooperative games. This paper describes benefits that result when coupling rational cooperation, under some situations, is increased. We prove that if a coupling game is strictly rational and partly cooperative, the higher the coupling factors, the larger the social payoff, which is the sum of the payoffs of all players. Other properties of cooperation in coupling game theory and possible applications are discussed.     

基于随机支付的合作博弈分析

在确定性支付的合作博弈中,Ｓｈａｐｌｅｙ值以其优良的特性在合作博弈分配解中占据着非常重要的作用,但现实生活中更多情形下的支付是不确定的,参与人要在这种情形下作出选择．因此,基于Ｓｈａｐｌｅｙ值的表述公式,构建基于随机支付的合作博弈模型,构造边际值和转换值两个合作解,并举例说明随机支付情形下两个解不再相等．最后,给出了两个解相等的一个博弈子类．     

基于微分博弈的双渠道广告合作协调策略研究

研究在制造商开通网上和零售渠道的情形下, 供应链成员的广告合作和成本分担对双渠道协调的影响. 研究结果表明, 无论零售商的广告对品牌形象产生何种影响, 制造商分担零售商的部分广告费用均能使得双方的利润优于分散决策的情形, 但不能完全实现双渠道协调. 此外, 当零售商也分担制造商的部分广告费用时, 双方均可以实现完全的协调. 相比于零售商频繁促销产生负面影响的情形, 在不产生负面影响的情况下, 双方能够实现更多的价值.