Price-based interference avoidance game in the Gaussian interference channel

This paper considers a distributed interference avoidance problem employing frequency assignment in the Gaussian interference channel(IC).We divide the common channel into several sub-channels and each user chooses one sub-channel for transmission in such a way that the total interference in the IC is minimum.This mechanism named interference avoidance in this paper can be modeled as a competitive game model.And a completely autonomous distributed iterative algorithm called distributed interference avoidance algorithm(DIA)is adopted to achieve the Nash equilibrium(NE)of the game.Due to the self-optimum,the DIA is a sub-optimal algorithm.Therefore,through introducing an optimal compensation(or price)into the competitive game model,we successfully develop a compensation-based game model to approximate the optimal interference avoidance problem.Moreover,an optimal algorithm called iterative optimal interference avoidance algorithm(IOIA)is proposed to reach the optimality of the interference avoidance scheme.We analyze the implementation complexity of the proposed algorithm which is only O(N),with N standing for the number of users in the IC.We also give the proof on the convergence of the proposed algorithm.The performance upper bound and lower bound are derived for the IOIA algorithm.The simulation results show that the IOIA does reach the optimality under the condition of interference avoidance mechanism.     

COMBINING TRUST MODELING AND MECHANISM DESIGN FOR PROMOTING HONESTY IN E‐MARKETPLACES

In this paper, we propose a novel incentive mechanism for promoting honesty in electronic marketplaces that is based on trust modeling. In our mechanism, buyers model other buyers and select the most trustworthy ones as their neighbors to form a social network which can be used to ask advice about sellers. In addition, however, sellers model the reputation of buyers based on the social network. Reputable buyers provide truthful ratings for sellers, and are likely to be neighbors of many other buyers. Sellers will provide more attractive products to reputable buyer to build their own reputation. We theoretically prove that a marketplace operating with our mechanism leads to greater profit both for honest buyers and honest sellers. We emphasize the value of our approach through a series of illustrative examples and in direct contrast to other frameworks for addressing agent trustworthiness. In all, we offer an effective approach for the design of e‐marketplaces that is attractive to users, through its promotion of honesty.     

Generous or Selfish?Weighing Transaction Forwarding Against Malicious Attacks in Payment Channel Networks

Journal of Computer Science and Technology - Scalability has long been a major challenge of cryptocurrency systems, which is mainly caused by the delay in reaching consensus when processing...     

基于后悔值的多Agent冲突博弈强化学习模型

对于冲突博弈,研究了一种理性保守的行为选择方法,即最小化最坏情况下Agent的后悔值.在该方法下,Agent当前的行为策略在未来可能造成的损失最小,并且在没有任何其他Agent信息的条件下,能够得到Nash均衡混合策略.基于后悔值提出了多Agent复杂环境下冲突博弈的强化学习模型以及算法实现.该模型中通过引入交叉熵距离建立信念更新过程,进一步优化了冲突博弈时的行为选择策略.基于Markov重复博弈模型验证了算法的收敛性,分析了信念与最优策略的关系.此外,与MMDP(multi-agent markov decision process)下Q学习扩展算法相比,该算法在很大程度上减少了冲突发生的次数,增强了Agent行为的协调性,并且提高了系统的性能,有利于维持系统的稳定.     

Strategic bidding in continuous double auctions

In this paper, we describe a novel bidding strategy that autonomous trading agents can use to participate in Continuous Double Auctions (CDAs). Our strategy is based on both short and long-term learning that allows such agents to adapt their bidding behaviour to be efficient in a wide variety of environments. For the short-term learning, the agent updates the aggressiveness of its bidding behaviour (more aggressive means it will trade off profit to improve its chance of transacting, less aggressive that it targets more profitable transactions and is willing to trade off its chance of transacting to achieve them) based on market information observed after any bid or ask appears in the market. The long-term learning then determines how this aggressiveness factor influences an agent's choice of which bids or asks to submit in the market, and is based on market information observed after every transaction (successfully matched bid and ask). The principal motivation for the short-term learning is to enable the agent to immediately respond to market fluctuations, while for the long-term learning it is to adapt to broader trends in the way in which the market demand and supply changes over time. We benchmark our strategy against the current state of the art (ZIP and GDX) and show that it outperforms these benchmarks in both static and dynamic environments. This is true both when the population is homogeneous (where the increase in efficiency is up to 5.2%) and heterogeneous (in which case there is a 0.85 probability of our strategy being adopted in a two-population evolutionary game theoretic analysis).     

基于博弈论的人员疏散演化研究

在人员疏散中,撤离者之间的冲突行为复杂且对疏散的速率影响较大,为了模拟此过程,提出了一种将博弈论与元胞自动机相结合的模型。在该模型中设置了两种策略的人（叛逃者和合作者）,并引入恐慌指数和惯性系数两个重要参数,来描述疏散过程中撤离者的恐慌和保持原策略的能力;每一次冲突即是一次博弈,发生冲突的撤离者之间通过收益矩阵来确定成功者;并且在博弈完成时采用费米函数进行策略更新。模型再现了“出口拱形”和“快即是慢”现象;同时发现在相同的恐慌下,叛逃者与合作者的比率总是倾向于一致状态。这些自组织现象支持了模型的正确性。该项工作也有助于理解惯性因素对于合作行为产生与存续的影响。     

一种异构多接口多信道无线网络的信道分配算法

多接口多信道技术是无线网络环境中减少链路干扰、提高网络吞吐量的有效途径,但如何合理有效地进行信道分配已成为多接口多信道无线网络所面临的主要问题之一.针对自私的网络节点,本文使用非合作博弈对异构条件下多接口节点的信道分配问题进行建模分析,其纳什均衡解为解决该问题所需的稳定的信道分配方案.本文首先讨论纳什均衡的存在条件并提出实现纳什均衡的分布式算法.此外,考虑到实际网络中节点仅能感知局部信道信息以及接口工作信道受限等因素,本文进一步改进算法并通过仿真实验对其收敛性进行证明.     

The introduction strategy of the emerging online marketplace considering risk attitude and channel power

With the development of online retailing, traditional online platforms have begun to offer a novel online marketplace format that brings many advantages but also gives rise to problems such as operational risks and changes in channel power. This paper studies whether the e-tailer and manufacturer can reach a consensus on introducing the marketplace channel and obtains the following insights. First, the manufacturer always prefers to introduce the online marketplace in the model where she acts as the leader. The e-tailer has the same preference for the online marketplace when he moves later or simultaneously with the manufacturer. Second, as the participants become more risk-averse, the manufacturer and e-tailer would be less willing to introduce the online marketplace, and it would be more difficult to realize the equilibrium strategy under all power structure models. Third, by combining the cross-effect of the attitude towards risks and the power structure, we find that when the participants prefer risks and the e-tailer has strong channel power, it would be much easier for the two parties to reach a consensus about introducing the online marketplace.     

多射频无线网络中多信道分配方法的研究

针对多射频多信道无线网络信道分配中用户收益不均衡和网络资源利用率低的问题,给出了一种基于博弈论的信道分配策略,该策略在考虑信道分配有效性、公平性的同时,基于不完美信息博弈,给出了一种使网络负载更均衡的算法,并通过实验仿真验证了算法的鲁棒性和有效性。     

The concept of and search for the fair distribution in cooperative games

Well-known conflict equilibria are used to formulate the concept of fair distribution, and a technique is proposed to find it in an arbitrary cooperative game. Any cooperative game is shown to have only one fair distribution, which can always be found from the formulas of conflict equilibrium theory. The study was carried out in line with the OITVS RAN program (Project No. 1-3) and was sponsored by the Russian Foundation for Basic Research (Project No. 06-01-00821). Translated from Kibernetika i Sistemnyi Analiz, No. 6, pp. 131–141, November–December 2008.     

Modeling Instrumental Rationality, Land Tenure and Conflict Resolution

Full instrumental rationality and perfect institutions are two cornerstoneassumptions underlying neoclassical models. However, in the real world, thesetwo assumptions never hold, especially not in developing countries. In thispaper, we develop a game theoretical model to investigate if relaxations inthe full instrumental rationality and perfect institutions premise can explainthe conflicts that have been occurring between the various principals in theNarok district in Kenya with regard to land tenure and use.     

供需链管理中合同定量研究及其发展

描述了供需合同在供需链分布决策中所起的作用,分析了几种常用合同策略的激励机制及相互关系．从合同策略形式、供需链结构建模、市场需求建模、采购供应过程建模、信息建模5个方面对供需合同问题的研究进展作了总结．最后分析了当前该领域存在的不足,指出了今后可能的研究方向．     

环境污染博弈问题的系统动力学模型*

用系统动力学建立环境污染管理问题中政府管理部门与生产排污企业之间的一个混合战略重复博弈模型,考虑信息延迟和环境的污染量净化问题进行模型的仿真。结果表明,环境污染问题中政府管理部门与生产排污企业之间博弈的Nash均衡实际上很难达到稳定,尤其是在考虑信息延迟的情况下。最后提出一种简单可行的双重惩罚策略,既可以促使博弈双方尽快达到Nash均衡,也能有效地改善环境污染问题。     

基于链链竞争的闭环供应链渠道结构选择策略

研究当零售商之间存在价格竞争时,两条竞争闭环供应链的渠道结构选择问题。结果表明：从供应链系统总利润角度出发,当两条链之间竞争强度较小时,中心化渠道结构占优;反之,分散化渠道结构占优。从消费者与环境的角度出发,无论两链之间竞争强度为何值,两条链同时选择中心化渠道结构时最有利。     

认知无线网络中基于Sigmoid函数的功率控制算法研究

为了实现认知无线网络中频谱分配公平性以及契合现代化绿色通信的需求,根据非合作博弈论和干扰温度,引入信道状态概念,设计出一种新型功率控制算法,分析了该算法的收敛性、纳什均衡解的存在性和唯一性;该算法不仅可以快速收敛,符合实时通信,而且分布式实施,简单实用; 仿真结果表明,相比其他算法,该算法系统干扰小,能源消耗低,具有抗干扰性能,而且在日益多用户网络的情况下,具有低功率、低干扰,提高网络的整体效益,更加符合现代化的绿色通信的需求。     

针对合作型无人机的最优防相撞策略

为解决复杂融合空域内的无人机(unmanned aerial vehicle,UAV)冲突解脱过程中消耗大的问题,提出基于速度障碍法的合作型无人机的最优防相撞策略.首先根据有限时间的速度障碍法进行冲突探测,并推导出解脱条件下冲突双方航向改变量与速度大小改变量满足的关系,再将合作博弈概念用在冲突解脱过程中,利用最优化理论...     

基于博弈论的频谱动态管理研究

随着无线通信技术的快速发展,无线频谱成为越来越紧缺的网络资源.现有的静态频谱管理机制导致频谱资源在空间维度和时间维度上的低利用率.拍卖机制被认为是解决频谱资源稀缺问题的行之有效的方法.然而,设计高效、实际的频谱拍卖机制需要考虑5个挑战：理性用户自私策略行为、信道异质特性、信道空间重用特性、用户偏好多样性和社会福利的最大化.对频谱拍卖机制的研究现状做了全面的综述,指出现有工作存在的问题,并提出可行的解决方案;展示了在异质频谱管理中的最新研究成果;将异质频谱的重分配问题建模成组合拍卖模型,结合5个设计难题提出高效的信道分配机制和定价策略.该机制实现了防策略性和近似社会福利最大化.     

一种最小化干扰数目的多无线电信道分配算法

无线Ad hoc网络中要求链路可以随机处于任何位置进行通信.由于链路位置的随机性,可能会造成某些链路都聚集在某个小范围内,同时通信可能会造成链路间相互干扰.因此需要一种机制来保证链路间实际干扰最小.针对此问题,在信道分配中运用了博弈的思想,利用位势博弈特性构建效用函数,对存在潜在干扰的链路分配信道,使实际干扰最小.算法通过不断循环改变链路无线电的信道,最小化实际干扰数目达到纳什均衡.仿真结果表明,算法能够使信道分配策略达到纳什均衡,使链路间通信拥有更高的吞吐量和更好的鲁棒性.