融资互换的Nash谈判解

本尝试将Nash谈判解应用到金融领域中，从对策论的角度解释和探讨了互换的源泉、机制和定价模型，提出互换过程即为一个求解Nash谈判解的过程，在不考虑风险和考虑风险的情况下，分别求出谈判双方的收益比。     

不确定性军事冲突模式预测的数学方法

本文在模糊集上研究了不确定性军事冲突态势的变化模式 ,即 Nash协商对策模式、协调模式、谈判偏好模式、谈判让步模式和战争模式 ;探讨了不同模式下对应的 Nash均衡域、协商域、偏好域、代价域和冲突域的数学意义 ,给出了不同模式下解确定的数学方法 ,从定量的角度实现了对军事冲突模式的判断和预测 .     

支付函数为模糊数的多目标多人合作对策的纳什谈判解

讨论了多目标多人合作对策中支付函数是模糊数的情形,利用模糊数学相关理论, 对Nash提出的6条公理进行拓广,并证明这种情况下λ-纳什谈判解的存在性.     

二人谈判问题

本文避开了Nash谈判公理,根据实际情况建立了支付可转让和支付不可转让两类谈判问题模型,并通过引入谈判因子,给出了类似的谈判解.     

产出不确定条件下“公司+农户”型订单农业供应链协商模型研究

在农产品产出不确定性及零售价格受农产品产出率影响的条件下,研究了一类由风险规避农户和风险中性公司组成“公司+农户”型订单农业农产品供应链协调问题。在该农产品供应链中,农户和公司通过Nash协商谈判来分别决策最优的生产量和订单价格。研究结果表明,在农产品产出不确定及零售市场价格受农产品产出率影响的条件下,风险规避型农户和公司的Nash协商合作博弈存在均衡解。Nash协商谈判所达成的最优农产品产出量和订单价格均高于分散决策情形下的最优农产品产出量和订单价格。最优农产品产出量是关于农户风险规避度的单调增函数,而最优的订单价格是关于农户风险规避度的单调减函数。最后,通过与分散决策情形相比,证明了Nash协商谈判机制能够促使风险规避型农户和风险中性型公司均达到帕累托改进。     

公平偏好下考虑互补效应的项目投资收益分配研究

决策者的公平偏好对项目投资合作的形成和推进有重要影响。本文从创业企业和风险投资家的双重道德风险出发,选取Nash谈判解为公平偏好参照点,构建创业企业具有公平偏好的项目投资委托代理模型,研究委托方和代理方的能力存在互补效应的情形下,公平偏好对项目收益分配及双方努力水平的影响。结果表明:项目收益的最优分配比例和双方的最高努力水平均与创业企业的公平偏好程度相关。在互补效应存在时,双方的努力水平不会随收益分配比例的变化呈现单调变化趋势。如果双方的能力互补程度较小,具有公平偏好的创业企业会以Nash谈判解为自己的收益下限,风险投资家需要向其让渡更多的项目收益才能实现有效激励;如果双方的能力互补程度较大,创业企业会将Nash谈判解作为自己的收益上限,风险投资家即使不给予其大于Nash谈判解的收益也可实现有效激励。     

数学游戏与最优策略

众所周知，我国古代"田忌与齐王赛马"是对策论的一个典型例子．在做数学游戏时运用对策论的思想方法就是如何取胜．例1桌上放着60根火柴，甲、乙轮流每次取1～3根，谁取到最后一根为优胜．如双方都采用最优策略、由甲先取，谁定能获胜？给出一种获胜方法．分析要想取到最后一根，必须先取到倒数第5根，因为在这以后对方只能取到倒数第4根、第3根或第2根，所以只要取到了倒数第5根，就已经是胜利在握了．同样要想取到倒数第5根，必须先取得倒数第9根，以此类推得：某方（倒数）：1；5；9；13，...对方（倒数）：2，3，4；6，7，8；10，11，12…     

求2~3-三矩阵对策Nash平衡解的方法

提出了求2~3-三矩阵对策Nash平衡解的方法.     

基于模糊方法的多人合作对策的研究

多人合作对策模型中联盟的收入和总体的收入常常出现相互矛盾的情况 ,此时核是空集 .由于不存在核 ,无法用 Nash-Harsanyi谈判模型求解 .采用模糊数学方法 ,调整模型中线性约束的右端系数 ,使核在一定程度上是非空集合 ,得到模糊意义下的 Nash平衡解 .该方法一定程度上解决了各联盟收入与总体收入的矛盾 .最后通过一个算例说明该方法的可行性 .     

基于连续同伦的多方对策之Nash均衡点的机械化求解方法

Nash定理证明非合作n人矩阵对策一定有混合平衡解,现有文献多讨论n=2时混合平衡解的求法,一般用优化或逼近的方法.文章给出了一种机械化求解方法,通过构造非合作多人矩阵对策的混合平衡局势所满足的多项式方程组,应用方程组求解软件由此可直接求出多人对策的问题的各种混合平衡解.     

Strategic Manipulation Approach for Solving Negotiated Transfer Pricing Problem

This paper suggests an approach for solving the transfer pricing problem, where negotiation between divisions is carried out considering the manipulation game theory model for a multidivisional firm. The manipulation equilibrium point is conceptualized under the Machiavellian social theory, represented by three concepts: views, tactics and immorality. In this approach, we are considering a non-cooperative model for the transfer pricing problem: a game model involving manipulating and manipulated players engaged cooperatively in a Nash game, restricted by a Stackelberg game. The cooperation is represented by the Nash bargaining solution. The transfer pricing problem is conceptualized as a strong Stackelberg game involving manipulating and manipulated divisions. This structure established conditions of unequal relative power among divisions, where high-power divisions tend to be abusive and less powerful divisions have a tendency to behave compliantly. For computation purposes, we transform the Stackelberg game model into a Nash game, where every division is able of manipulative behavior to some degree: the Nash game relaxes the interpretation of the manipulation game and the equilibrium selection for the transfer pricing problem. The manipulation dynamics and rationality proposed for the transfer pricing problem correspond to many real-world negotiation situations. We present an example, that illustrates how manipulation can be employed to solve the transfer pricing problem in a multidivisional firm.     

Computing Nash equilibria through computational intelligence methods

Nash equilibrium constitutes a central solution concept in game theory. The task of detecting the Nash equilibria of a finite strategic game remains a challenging problem up-to-date. This paper investigates the effectiveness of three computational intelligence techniques, namely, covariance matrix adaptation evolution strategies, particle swarm optimization, as well as, differential evolution, to compute Nash equilibria of finite strategic games, as global minima of a real-valued, nonnegative function. An issue of particular interest is to detect more than one Nash equilibria of a game. The performance of the considered computational intelligence methods on this problem is investigated using multistart and deflection.     

运输问题的合作对策求解方法

产地间或销地间往往存在竞争,在这种情况下,使用运输问题最优化方法是不合理的。因此,从个体理性的视角提出运输问题的合作对策求解方法,方法将运输问题看作是一个博弈问题,各个产地或销地是博弈的局中人,求解其纳什均衡与纳什讨价还价解。在此基础上,说明了运输问题的非合作形式是一个指派问题,并证明指派问题的最优解是一个纳什均衡点。接着,通过实验验证运输问题的最优解是一个纳什讨价还价解,满足产地或销地的自身利益。在此基础上,针对纳什讨价还价解不唯一的问题,从决策者的视角给出最大可能激励成本的计算方法。最后,为弥补纳什讨价还价解不唯一及纳什讨价还价解不允许出现子联盟的缺陷,给出运输收益分配或成本分摊的Shapely值计算方法。     

A two-person non-zero-sum game model of the world oil market

The world oil market is modelled as a two-person non-zero-sum game in normal form with each player having a continuum of strategies. The two players are the oil importing nations (OPIC) and the oil exporting nations (OPEC). The game is solved in the noncooperative sense using the equilibrium point solution concept due to Nash. The Nash equilibrium point solution yields an analytic expression for the optimal price per barrel of oil for OPEC and the optimal level of imports of oil for OPIC assuming noncooperation between the players. The cooperative solution to the game is also investigated using the von Neumann-Morgenstern negotiation set solution and Nash's bargaining point solution. Again, we give analytic expressions for the optimal price of a barrel of oil and the optimal level of imports of oil assuming that the players cooperate (negotiate, bargain, etc., for a binding agreement) in arriving at a solution.     

指派问题的纳什均衡解

为弥补传统指派问题解不符合个体理性的不足,提出指派问题的纳什均衡解,并证明有限指派问题有且仅有纯纳什均衡解。相比传统的指派问题解,纯纳什均衡符合Pareto最优,是个体理性视角下的最优解。在此基础上,给出一个综合考虑个体理性与集体理性的求解方法。     

Variational inequality formulation for the games with random payoffs

We consider an n-player non-cooperative game with random payoffs and continuous strategy set for each player. The random payoffs of each player are defined using a finite dimensional random vector. We formulate this problem as a chance-constrained game by defining the payoff function of each player using a chance constraint. We first consider the case where the continuous strategy set of each player does not depend on the strategies of other players. If a random vector defining the payoffs of each player follows a multivariate elliptically symmetric distribution, we show that there exists a Nash equilibrium. We characterize the set of Nash equilibria using the solution set of a variational inequality (VI) problem. Next, we consider the case where the continuous strategy set of each player is defined by a shared constraint set. In this case, we show that there exists a generalized Nash equilibrium for elliptically symmetric distributed payoffs. Under certain conditions, we characterize the set of a generalized Nash equilibria using the solution set of a VI problem. As an application, the random payoff games arising from electricity market are studied under chance-constrained game framework.     

On the Selection of One Feedback Nash Equilibrium in Discounted Linear-Quadratic Games

We study a selection method for a Nash feedback equilibrium of a one-dimensional linear-quadratic nonzero-sum game over an infinite horizon. By introducing a change in the time variable, one obtains an associated game over a finite horizon T > 0 and with free terminal state. This associated game admits a unique solution which converges to a particular Nash feedback equilibrium of the original problem as the horizon T goes to infinity.     

A model of a general parimutuel system: Characterizations and equilibrium selection

We formulate a model of a parimutuel system which considers a horse race with two horses. In our model, the raceholder offers a rate of his total betting revenue in the first stage. In the second stage each bettor simultaneously decides whether he bets one unit of money on one horse or he withdraws, according to his win predictions for each horse. We assume that all bettor's predictions are different and are common knowledge. We define some types of equilibria in the second stage game and give necessary and sufficient conditions for their existence. One equilibrium is a selected as a solution for the second stage game. We also define a solution for the whole game by using this result. Finally, we analyze the relation between the solution and variance for the bettor predictions.We thank to Prof. Okada, A. and Ikebe, Y. for helpful discussions. Special thanks are due to an anonymous referee for very grateful comments.     

分布参数最优控制的边界元共轭梯度算法

研究了一类线性椭圆型分布参数最优控制问题的数值解算法.得到最优控制对应的最优性方程组,在凸性条件下,证明了最优控制的唯一存在性问题.将最优控制问题化为以控制函数和状态函数为局中人的递阶式(Stackelberg)非合作对策问题,其平衡点是最优控制的解.进一步得到求平衡点的边界元共轭梯度算法.最后,研究算法中边界元离散的误差估计,以算例验证该算法.     

Sequential Linear-Quadratic Method for Differential Games with Air Combat Applications

We present a numerical method for computing a local Nash (saddle-point) solution to a zero-sum differential game for a nonlinear system. Given a solution estimate to the game, we define a subproblem, which is obtained from the original problem by linearizing its system dynamics around the solution estimate and expanding its payoff function to quadratic terms around the same solution estimate. We then apply the standard Riccati equation method to the linear-quadratic subproblem and compute its saddle solution. We then update the current solution estimate by adding the computed saddle solution of the subproblem multiplied by a small positive constant (a step size) to the current solution estimate for the original game. We repeat this process and successively generate better solution estimates. Our applications of this sequential method to air combat simulations demonstrate experimentally that the solution estimates converge to a local Nash (saddle) solution of the original game.