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 ac- cording 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 play- ers, 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.

THE OPTIMAL CONTROL FOR PROMOTING THE COOPERATION IN EVOLUTION GAME GENERATED BY PRISONER'S DILEMMA

Natural selection opposes the evolution of cooperation unless specific mechanisms are at work in Prisoner＇s Dilemma. By taking advantage of the modern control theory, the controller design is discussed and the optimal control is designed for promoting cooperation based on the recent advances in mechanisms for the evolution of cooperation. Two con- trol strategies are proposed： compensation control strategy for the cooperator when playing against a defector and reward control strategy for cooperator when playing against a coop- erator. The feasibility and effectiveness of these control strategies for promoting cooperation in different stages are analyzed. The reward for cooperation can＇t prevent defection from being evolutionary stable strategy （ESS）. On the other hand, compensation for the coopera- tor can＇t prevent defection from emerging and sustaining. By considering the effect and the cost, an optimal control scheme with constraint on the admissible control set is put forward. By analyzing the special nonlinear system of replicator dynamics, the exact analytic solution of the optimal control scheme is obtained based on the maximum principle. Finally, the effectiveness of the proposed method is illustrated by examples.

System dynamics of behaviour-evolutionary mix-game models

In real financial markets there are two kinds of traders： one is fundamentalist, and the other is a trend-follower. The mix-game model is proposed to mimic such phenomena. In a mix-game model there are two groups of agents： Group 1 plays the majority game and Group 2 plays the minority game. In this paper, we investigate such a case that some traders in real financial markets could change their investment behaviours by assigning the evolutionary abilities to agents： if the winning rates of agents are smaller than a threshold, they will join the other group; and agents will repeat such an evolution at certain time intervals. Through the simulations, we obtain the following findings： （i） the volatilities of systems increase with the increase of the number of agents in Group 1 and the times of behavioural changes of all agents; （ii） the performances of agents in both groups and the stabilities of systems become better if all agents take more time to observe their new investment behaviours; （iii） there are two-phase zones of market and non-market and two-phase zones of evolution and non-evolution; （iv） parameter configurations located within the cross areas between the zones of markets and the zones of evolution are suited for simulating the financial markets.

EVOLUTIONARY PUBLIC GOODS GAMES BASED ON HISTORICAL PAYOFFS

We investigate the evolution of cooperation in public goods game based on individuals' historical payoffs. In particular, the fitness of individuals are characterized by two types of payoffs, which are obtained by acting as cooperators and defectors, respectively. Both of payoffs are the linear combination of the current payoffs and the cumulative historical payoffs. The results show that cooperation is enhanced by an increasing memory effect with a wide range of related factors. To explain this phenomenon, we plot some representative snapshots of the population and scrutinize the mean fitness of cooperators and defectors along the boundary. It is found that increasing memory effect induces a positive feedback mechanism for cooperators to expand their districts. Defectors can just survive through forming narrower clusters to exploit cooperators more widely. The threshold values for cooperators and defectors vanishing under the influence of noise are also investigated.

Solving the Balance Problem of On-Line Role-Playing Games Using Evolutionary Algorithms

In on-line role-playing games (RPG), each race holds some attributes and skills. Each skill contains several abilities such as physical damage, hit rate, etc. Parts of the attributes and all the abilities are a function of the character’s level, which are called Ability-Increasing Functions (AIFs). A well-balanced on-line RPG is characterized by having a set of well-balanced AIFs. In this paper, we propose an evolutionary design method, including integration with an improved Probabilistic Incremental Program Evolution (PIPE) and a Cooperative Coevolutionary Algorithm (CCEA), for on-line RPGs to maintain the game balance. Moreover, we construct a simplest turn-based game model and perform a series of experiments based on it. The results indicate that the proposed method is able to obtain a set of well-balanced AIFs efficiently. They also show that in this case the CCEA outperforms the simple genetic algorithm, and that the capability of PIPE has been significantly improved through the improvement work.

Adaptive co-evolution of strategies and network leading to optimal cooperation level in spatial prisoner's dilemma game

We study evolutionary prisoner＇s dilemma game on adaptive networks where a population of players co-evolves with their interaction networks. During the co-evolution process, interacted players with opposite strategies either rewire the link between them with probability p or update their strategies with probability 1 - p depending on their payoffs. Numerical simulation shows that the final network is either split into some disconnected communities whose players share the same strategy within each community or forms a single connected network in which all nodes are in the same strategy. Interestingly, the density of cooperators in the final state can be maximised in an intermediate range of p via the competition between time scale of the network dynamics and that of the node dynamics. Finally, the mean-field analysis helps to understand the results of numerical simulation. Our results may provide some insight into understanding the emergence of cooperation in the real situation where the individuals＇ behaviour and their relationship adaptively co-evolve.

基于演化博弈的我国分级诊疗策略分析

目的在分级诊疗制度中涉及政府、医院和患者之间的利益关系,探讨三方动态博弈策略,有利于完善分级诊疗的理论范式和政策逻辑。方法构建政府、医院和患者三方模型,分析其策略选择及演化路径,求解三方演化博弈的稳定策略,探究如何进行利益平衡和合作以实现三方共赢。另外,利用Matlab R2018b对模型进行仿真,进一步分析三方主体的演化路径以及不同策略选择对分级诊疗制度推广的影响。结果政府、医院和患者3个主体的决策行为之间相互影响,最终将演化至点(1,1,1)的理想稳定状态。增大政府补贴会加速医院和患者的初始参与概率值收敛至1,但过多的补贴会使政府逐渐背离鼓励分级诊疗的策略。结论政府应在成本范围内加大对医院优质医疗资源下沉的专家补贴力度,并加强政府监管。大型医院和基层医疗卫生机构重要的是实现医生资源的自由流动和合理分布。患者还需转变固有的就医观念,才能最终实现有序就医。

住宅部品生产商质量认证行为扩散研究

认证是提升住宅部品质量的有效手段,其扩散推广有利于住宅产业供给侧转型升级。为探究质量认证行为在住宅部品生产商间的扩散机理,本文引入复杂网络演化博弈理论构建了住宅部品质量认证扩散模型。通过数值仿真分析了市场导向和政府激励影响下质量认证行为在住宅部品生产商间的扩散过程。结果表明:消费者溢价、认证影响力与政府激励在一定范围内均可有效促进质量认证行为在住宅部品生产商间的正向扩散,其中生产商对消费者溢价的变化最为敏感。最后,通过分析住宅部品生产商质量认证行为扩散的演化特征,对质量认证在住宅部品生产领域的推广提出实质性对策与建议。研究从市场和政府两方面拓展了住宅部品生产商质量认证行为扩散的理论研究体系,促进了住宅高质量发展的理论实践。

数字经济下个人信息使用和保护平衡的三方演化博弈分析

构建以政府(G)、个人信息所有者(P)和个人信息获取/使用者(C)三方为主体的动态博弈模型,分析其演化过程。通过对以政府为驱动的三方博弈的演化路径分析,从三方的角度分别提出对策建议。研究结果表明,政府实施严格监管可以提升自身形象和管理效率。政府应主要采用惩罚手段,使个人信息获取/使用者在违规策略下产生较高的成本,从而促使他们采取规范获取和使用的策略。对于个人信息所有者而言,政府及时发现违规行为并严格处理,同时积极宣传个人信息维护,可激励他们采取积极提供个人信息的策略。在这种情况下,三方可实现帕累托最优的策略均衡,并实现在数字经济下个人信息使用和保护的平衡。

基于演化博弈的民航危险品运输培训监管

为促进民航危险品运输培训精准监管,提升民航监管效能,实现合规培训与监管的最佳局面,进一步保障航空运输安全。首先从行为交互和微观经济学的角度,运用演化博弈方法,构建危险品运输培训机构和民航局双方演化博弈模型,定量分析博弈双方行为策略选择的情境条件及形成原因;然后运用MATLAB软件对重要参数的敏感性进行数值仿真分析,探讨受训者能力不足造成不安全事件概率、查处成功率、处罚力度和监管成本4个重要参数对系统演化路径及结果的影响效应;最后从管理层面对民航危险品运输培训监管提出有针对性的建议及措施。结果表明:受训者能力不足造成不安全事件概率、查处成功率和处罚力度3个参数对博弈双方行为选择具有正效应,而监管成本对博弈双方行为选择具有负效应。

基于网络演化博弈的信息传播行为分析

演化博弈论将博弈理论与动态演化过程相结合,在演化的过程中追求动态平衡,该方法较好地实现了对在线社交网络信息传播演化趋势的分析。为了进行在线社交网络中的信息传播演化动力学研究,同时分析到达某一均衡状态的原因和方式,首先结合在线社交网络特性构建改进聚集的无标度网络,用户间的交互采用单参数囚徒困境博弈模型,并采用费米规则更新策略。其次,通过数据仿真对影响网络中合作者比例演化的因素进行分析,得到网络聚集性、博弈收益权重会促进网络中的合作行为,而背叛诱惑与噪声因子则对其有抑制作用的结论。最后,结合新浪微博的真实舆论传播数据,对现实网络进行信息传播分析。研究表明,合作者比例是由博弈动力学和网络拓扑结构共同作用的结果,需采取适当的激励机制,以解决在线社交网络中信息传播出现的合作困境。

历史社会学视野下的PLAY,GAME,SPORT形态演变分析

通过历史社会学的视角,分析体育运动PLAY,GAME,SPORT的形态演变。从演变关系上,对一项体育运动和整个体育运动的演变发展进行图析;从界限划分上,确定不同时期体育运动的社会形态和代表形态;从特征比较上,进行PLAY与SPORT,GAME与SPORT之间的特征形态分析。以此探求体育运动PLAY,GAME,SPORT形态演变的内部动力,主要反映在暴力化,权力再分配以及表象性与模拟性。三者的形态演变在一项体育运动的发展以及整个体育运动的发展表现是不同的,并体现出文明的进程。

多主体博弈下基于改进灰狼算法的综合能源服务商优化运行策略

为促进新能源消纳和满足不同负荷需求,本文提出了多主体博弈下的综合能源服务商优化运行策略。通过分析不同主体的交互及利益关系,建立综合能源服务商与分布式发电商、负荷用户的主从博弈双层优化模型,上层综合能源服务商通过售能价格激励下层负荷用户调整用能需求,并以高于新能源上网电价的购电价格激励下层分布式发电商进行售电量调整。针对模型的高维、非线性特征,通过引入差分进化和精英保留策略加速灰狼算法的全局搜索能力和收敛性。仿真结果表明所建模型在兼顾不同主体利益的同时,降低了系统的碳排放量,所提优化求解方法快速高效。

颠覆性创新中政府、企业与消费者三方的博弈关系和决策演化机制

颠覆性创新需要政府、企业、消费者的共同参与和深度协作,厘清三方主体在颠覆性创新中的博弈关系和决策演化机制是进一步优化颠覆性创新环境、推动企业开展颠覆性创新的关键问题。然而现有颠覆性创新研究主要聚焦于技术突破层面,未把颠覆性创新置于真实的市场环境下,普遍忽略了消费者这一关键核心要素。因此,基于博弈论构建政府、企业、消费者三方的颠覆性技术创新决策动态演化博弈矩阵,综合考量三方的协同与竞争关系,并结合数值仿真阐释三方博弈策略演化过程,探讨3个关键变量——增加的政府补贴总额、企业挪用政府补贴用于渐进性创新需要付出的额外损失、企业颠覆性创新成功概率,剖析不同博弈主体在颠覆性创新中的策略选择、演化趋势和稳定条件。结果表明:短期内少量政府补贴能够刺激企业开展颠覆性创新,但长期性、大力度补贴容易导致企业对公共资源产生依赖,并增加投机风险,同时政府在支持颠覆性创新上相较于企业具有更大的试错空间,但也需要承担补贴带来的财政压力;消费者需求对颠覆性创新具有决定性作用,消费者认可的产品能够对企业决策产生根本性影响。因此,政府应谨慎评估潜在颠覆性创新的机遇和风险,以营造良好创新环境为第一优先事项,充分发挥市场在颠覆性创新中的决定作用。

考虑碳市场交易的寡头电力市场均衡分析

在碳市场上线的背景下,发电商需同时参与碳市场与电力市场,并对电力市场均衡产生影响。为研究碳市场及电力市场中发电商的交易决策及两个市场之间的交互影响关系,建立了考虑碳市场交易的寡头电力市场双层均衡模型,该模型可同时考虑发电商在电力市场和碳市场中的博弈行为。针对所建立模型,采用协同进化算法进行纳什均衡的求解。最后通过算例验证了相关模型和算法的有效性,并重点研究了碳市场对电力市场均衡及发电商市场博弈行为的影响。结果表明:在当前采用基准线法进行初始碳配额分配情况下,发电商的策略性行为同时抬高了电价与碳价,其中电价的上涨幅度远小于碳价的上涨幅度。

网络安全前沿技术演进机理与发展策略

根据信息技术和安全技术的“中介性”“调节性”本质,通过归纳总结指出网络安全前沿技术具备战略性、窗口性、交织性、颠覆性、对抗性等特征。围绕网络安全紧前威胁和中长期风险在运动发展中形成的对立统一关系,从技术演进的动因、逻辑和路径考察技术生长和存续机理。针对攻防双方在对抗场景中的优势争夺,通过4个“是否有利于”归纳网络安全技术演进的内在逻辑,给出网络安全前沿技术发展策略,以应对后疫情时期逆全球化、单边主义、保护主义思潮暗流涌动世界环境下网络空间安全技术的突围挑战。

网络媒体平台管控行为的随机演化博弈决策研究

[目的/意义]网络媒体平台在突发公共事件中发挥着重要作用。通过对不确定环境下网络媒体平台管控行为的随机演化博弈分析,为网络媒体平台舆论管控提供建议。[方法/过程]基于Moran过程的随机演化模型,将自然选择规则作为策略更新规则,探讨了影响网络媒体平台管控行为的因素,分析了外部随机性因素和内部因素主导情境下的均衡结果。[结果/结论]研究发现,网络媒体平台管控行为主要受外部随机性因素、平台数量规模、不同管控行为的成本收益影响。外部随机性越小、平台管控收益越大且成本越小,积极管控的扎根概率就越大,平台数量规模存在着一个能够有效管控突发公共事件的临界值,能为突发公共事件中网络媒体平台管控提供新思路。

Exploring Biocomplexity in Cancer: A Comprehensive Review

Living objects have complex internal and external interactions. The complexity is regulated and controlled by homeostasis, which is the balance of multiple opposing influences. The environmental effects finally guide the self-organized structure. The living systems are open, dynamic structures performing random, stationary, stochastic, self-organizing processes. The self-organizing procedure is defined by the spatial-temporal fractal structure, which is self-similar both in space and time. The system’s complexity appears in its energetics, which tries the most efficient use of the available energies;for that, it organizes various well-connected networks. The controller of environmental relations is the Darwinian selection on a long-time scale. The energetics optimize the healthy processes tuned to the highest efficacy and minimal loss (minimalization of the entropy production). The organism is built up by morphogenetic rules and develops various networks from the genetic level to the organism. The networks have intensive crosstalk and form a balance in the Nash equilibrium, which is the homeostatic state in healthy conditions. Homeostasis may be described as a Nash equilibrium, which ensures energy distribution in a “democratic” way regarding the functions of the parts in the complete system. Cancer radically changes the network system in the organism. Cancer is a network disease. Deviation from healthy networking appears at every level, from genetic (molecular) to cells, tissues, organs, and organisms. The strong proliferation of malignant tissue is the origin of most of the life-threatening processes. The weak side of cancer development is the change of complex information networking in the system, being vulnerable to immune attacks. Cancer cells are masters of adaptation and evade immune surveillance. This hiding process can be broken by electromagnetic nonionizing radiation, for which the malignant structure has no adaptation strategy. Our objective is to review the different sides of living complexity and use the knowledge to fight against cancer.

区块链游戏生态的角色动态识别与演化分析——以Axie Infinity为例

针对区块链游戏生态的复杂性,提出一种基于时序有向加权网络的新型角色识别方法。该方法首先设计了节点投票算法ChainVoteRank以识别出关键基础角色,然后结合多特征融合的层次聚类算法挖掘潜在的隐蔽角色。以play-to-earn(P2E)模式区块链游戏Axie Infinity为对象进行研究,结果表明该P2E模式区块链游戏生态中存在6种基本角色:劳工、正常玩家、经理、繁育商、交易商和机构组织。相较于传统角色识别方法,该方法不仅可以更好地识别出区块链游戏生态中的主要用户角色,而且还揭示了P2E模式区块链游戏生态的角色演化过程、不同阶段中各角色发挥的作用,以及P2E生态日益严重的贫富差距。