Femtocell网络的鲁棒议价博弈功率控制

针对具有不完美信道状态信息的Femtocell双层网络，为了保证网络效用最大化、最小服务质量要求及Femtocell用户之间的效用公平，提出了基于议价博弈的鲁棒功率控制方案.在保证宏小区用户正常传输情况下，考虑到Femtocell家庭用户的最小服务质量要求，将Femtocell网络的鲁棒功率控制问题转化为议价博弈功率控制问题.为了保证Femtocell家庭用户之间的公平性，给出了Kalai-Smorodinsky（K-S）议价博弈解，证明了议价博弈解的存在性和唯一性，并提出了一种基于二分查找算法的分布式鲁棒功率控制方案.仿真结果表明，所提出的算法不仅具有较好的收敛性能，而且能够较好地保证用户之间的公平性.     

Deep reinforcement learning-based cooperative interactions among heterogeneous vehicular networks

Most real-world vehicle nodes can be structured into an interconnected network of vehicles. Through structuring these services and vehicle device interactions into multiple types, such internet of vehicles becomes multidimensional heterogeneous overlay networks. The heterogeneousness of the overlays makes it difficult for the overlay networks to coordinate with each other to improve their performance. Therefore, it poses an interesting but critical challenge to the effective analysis of heterogeneous virtual vehicular networks. A variety of virtual vehicular networks can be easily deployed onto the native network by applying the concept of SDN (Software Defined Networking). These virtual networks reflect their heterogeneousness due to their different performance goals, and they compete for the same physical resources of the underlying network, so that a sub-optimal performance of the virtual networks may be achieved. Therefore, we propose a Deep Reinforcement Learning (DRL) approach to make the virtual networks cooperate with each other through the SDN controller. A cooperative solution based on the asymmetric Nash bargaining is proposed for co-existing virtual networks to improve their performance. Moreover, the Markov Chain model and DRL resolution are introduced to leverage the heterogeneous performance goals of virtual networks. The implementation of the approach is introduced, and simulation results confirm the performance improvement of the latency sensitive, loss-rate sensitive and throughput sensitive heterogeneous vehicular networks using our cooperative solution.     

装配式建筑外部效益分配问题研究——基于讨价还价博弈

基于外部性理论,提出装配式建筑产生的外部效益应该在各利益方之间均衡分配,实现外部效益向内部化转换,从而激发各利益主体推广装配式建筑的热情。在系统分析装配式建筑产生的外部效益的基础上,构建了政府、开发商和消费者三方之间的讨价还价博弈模型。现阶段只有满足开发商及消费者的最佳期望效益值,才能不断促使装配式建筑增量及转型。因此,为寻求最优的外部效益分配方案,构建了两种不同的博弈模型。一种是基于三大利益方的共同博弈模型,另一种是开发商与消费者达成短暂联盟与政府进行的讨价还价博弈。实证研究表明,开发商与消费者形成联盟方对分配结果有较大的影响。当开发商和消费者达成短暂联盟进行博弈时双方的分配额度都将增加,从而极大地增加了参与装配式建筑的积极性。     

Nash bargaining model for direct electricity trading on distribution side with multi-microgrids participation

随着售电侧电力市场改革的不断深入，研究多微电网参与下的配电侧直接电能交易具有重要意义。针对多微电网与负荷聚合商之间的直接电能交易，以各主体在传统交易方式下的最优效益作为谈判破裂点，提出了一种基于合作博弈论的纳什议价模型，模型中博弈参与者可获得帕累托最优效益。模型为非线性非凸问题，不易直接求解，将其分成求解支付和联盟效益最大化两个子问题。为保护交易主体内部隐私，联盟效益最大化问题采用交替方向乘子法进行分布式求解，交易双方在求解过程中仅需相互交换期望的交易电量。仿真结果表明该模型可以有效地提升交易双方的运营效益。     

Cooperative games with nontransferable utility on antimatroids

This paper introduces a new family of nontransferable utility (NTU) games with partial cooperation. Games with transferable utility (TU) restricted by antimatroids were studied since 2004. Antimatroids are known combinatorial structures which are interpreted in games as dependency situations among a group of agents, and they generalize several other hierarchical structures studied in the literature. Now we define projected NTU games over antimatroids following the same idea. We have needed to build a new theory about projections between two coalitions. In this case, an outcome is feasible for a coalition if and only if its projection is feasible in the NTU game. This paper studies several properties of the projected games and the relations between these games and the original game for some interesting cases: TU games, hyperplane games and bargaining problems.     

Game-theoretic solutions through intelligent optimization for efficient resource management in wireless visual sensor networks

We propose a quality-driven cross-layer optimization scheme for wireless direct sequence code division multiple access (DS-CDMA) visual sensor networks (VSNs). The scheme takes into account the fact that different nodes image videos with varying amounts of motion and determines the source coding rate, channel coding rate, and power level for each node under constraints on the available bit rate and power. The objective is to maximize the quality of the video received by the centralized control unit (CCU) from each node. However, since increasing the power level of one node will lead to increased interference with the rest of the nodes, simultaneous maximization of the video qualities of all nodes is not possible. In fact, there are an infinite number of Pareto-optimal solutions. Thus, we propose the use of the Nash bargaining solution (NBS), which pinpoints one of the infinite Pareto-optimal solutions, based on the stipulation that the solution should satisfy four fairness axioms. The NBS results in a mixed-integer optimization problem, which is solved using the particle swarm optimization (PSO) algorithm. The presented experimental results demonstrate the advantages of the NBS compared with alternative optimization criteria.     

Nash bargaining solution based multi-cell and multi-user interference alignment scheme for cellular networks

In wireless cellular networks, the interference alignment （IA） is a promising technique for interference management. A new IA scheme for downlink cellular network with multi-cell and multi-user was proposed, in the proposed scheme, the interference in the networks is divided into inter-cell interference （ICI） among cells and inter-user interference （IUI） in each cell. The ICI is aligned onto a multi-dimensional subspace by multiplying the ICI alignment precoding matrix which is designed by the singular value decomposition （SVD） scheme at the base station （BS） side. The aligned ICI is eliminated by timing the interference suppression matrix which is designed by zero-forcing （ZF） scheme at the user equipment （UE） side. Meanwhile, the IUI is aligned by multiplying the IUI alignment precoding matrix which is designed based on Nash bargaining solution （NBS） in game theory. The NBS is solved by the particle swarm optimization （PSO） method. Simulations show that, compared with the traditional ZF IA scheme, the proposed scheme can obtain higher data rate and guarantee the data rate fairness of UEs with little additional complexity.     

信息更新条件下零售商间调货利益分配

研究在产品市场信息更新条件下,通过零售商之间协调调货行为可减低销售风险,增加销售利润,提高产品市场服务率.应用Nash讨价博弈模型进行研究,得出结论:零售商之间调货可有效增加其销售盈利;在一般Nash讨价还价策略下,实现其利益合理分配的调货价格是存在的.     

Adaptive Online Voltage Scaling Scheme Based on the Nash Bargaining Solution

In an effort to reduce energy consumption, research into adaptive power management in real‐time systems has become widespread. In this paper, a novel dynamic voltage scaling scheme is proposed for multiprocessor systems. Based on the concept of the Nash bargaining solution, a processor's clock speed and supply voltage are dynamically adjusted to satisfy these conflicting performance metrics. In addition, the proposed algorithm is implemented to react adaptively to the current system conditions by using an adaptive online approach. Simulation results clearly indicate that the superior performance of the proposed scheme can strike the appropriate performance balance between contradictory requirements.     

The finer points of lying online: E-mail versus pen and paper.

The authors present 3 experimental studies that build on moral disengagement theory by exploring lying in online environments. Findings indicate that, when e-mail is compared with pen and paper communication media (both of which are equal in terms of media richness, as both are text only), people are more willing to lie when communicating via e-mail than via pen and paper and feel more justified in doing so. The findings were consistent whether the task assured participants that their lie either would or would not be discovered by their counterparts. Implications for theory and practice are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)