带策略约束的区间数双矩阵博弈的双线性规划求解方法

传统区间数双矩阵博弈理论研究局中人支付值为区间数的策略选择问题,但没有考虑局中人策略选择可能受到各种约束.创建一种求解局中人策略选择受约束且支付值为区间数的双矩阵博弈(简称带策略约束的区间数双矩阵博弈)的简单、有效的双线性规划求解方法.首先,将局中人的博弈支付看作支付值区间中数值的函数.通过证明这种函数具有单调性,据此利用支付值区间的上、下界,构造了一对辅助双线性规划模型,可分别用于显式地计算任意带策略约束的区间数双矩阵博弈中局中人区间数博弈支付的上、下界及其相应的最优策略.最后,利用考虑策略约束条件下企业和政府针对发展低碳经济策略问题的算例,通过比较其与不考虑策略约束情形下的结果,说明了提出的模型和方法的有效性、优越性及可应用性.     

具有风险偏好的梯形直觉模糊双矩阵对策模型及解法

在对策问题中,行动方案的选择不可避免的需要对预期支付值(收益值)进行估计和排序,且选择结果往往受到现实局中人风险偏好程度的影响.因此,该文针对局中人具有风险偏好及支付值为梯形直觉模糊的双矩阵对策进行了模型及求解方法的探讨.首先,提出了具有风险偏好的梯形直觉模糊数排序方法,再利用双线性规划求解方法,对梯形直觉模糊双矩阵对策进行求解.最后以企业营销策略选择为例,表明了该方法的有效性和实用性.     

考虑决策者风险态度的三角直觉模糊双矩阵博弈均衡及应用

在现实博弈问题中,行动方案的选择不可避免的需要对预期支付值(收益值)进行估计和排序,且选择结果往往受到决策者风险态度有的影响。针对决策者具有不同风险态度的博弈环境,基于模糊值指标和模糊度指标确定的三角直觉模糊数排序关系,研究了具有风险态度的三角直觉模糊双矩阵博弈模型,并利用双线性规划方法,给出了该环境下的均衡策略确定方法,为现实博弈均衡的确定提供了有效的途径。最后通过企业营销策略选择的应用研究,对方法的现实有效性予以说明。     

多重因素约束下的网格检查对策问题研究

基于物品数量及每列容量等限制因素,构造局中人的可行策略集合;考虑隐藏成本,处罚规则与检查成功概率等因素,构造相应的支付函数,建立多重因素约束下的网格检查对策模型.根据矩阵对策性质,将对策论问题转化为非线性整数规划问题,利用H(o|¨)lder不等式获得实数条件下的规划问题的解,然后转化为整数解,得到特定条件下的模型的对策值及局中人的最优混合策略.最后,给出一个实例,说明上述模型的实用性及方法的有效性.     

基于IITFN的模糊矩阵博弈最优策略研究

由于矩阵博弈支付函数具有模糊性,本文依据区间直觉梯形模糊数(IITFN)的基本理论,用区间直觉梯形模糊数来表示模糊矩阵博弈(FMG)支付函数;基于得分函数与精确函数提出了区间直觉梯形模糊矩阵博弈(IITFN-FMG)的策略最优解的求取方法。通过实例仿真,结果表明:以区间直觉梯形模糊数表示支付函数来分析最优策略如何选取,其效果更好,与实际情形的吻合程度亦更为理想。     

带风险偏好的区间支付交流结构合作博弈及平均树解北大核心CSCD

针对具有区间支付的限制结盟合作博弈,考虑现实局中人的不同偏好信息,通过引入风险偏好均值,提出了具有风险偏好的区间支付交流结构合作博弈及其平均树解.通过公理化体系对此解的存在性进行了证明,并将此分配方法应用到供应链纵向研发合作企业收益分配的实例中,表明该方法的有效性和可行性.此研究同时考虑了合作结盟的限制约束性和局中人的风险态度差异性,不仅能有效刻画现实结盟情境,且利于分配收益函数的求解.     

多重因素约束下的网格搜索对策问题研究

首次基于搜索成本及搜索资源等限制因素,构造局中人面向多重约束条件的可行策略集合,建立相应的搜索空间;在给定搜索点权值的基础上,考虑搜索成本与搜索成功概率等因素,构造相应的支付函数,建立多重因素约束下的网格搜索对策模型.为简化模型求解,将对策论问题转化为约束最优化问题,求解约束问题获得最优值,转化为模型的对策值,并给出双方最优混合策略.最后,给出军事想定实例,说明上述模型的实用性及方法的有效性.     

带风险偏好的区间支付交流结构合作博弈及平均树解

针对具有区间支付的限制结盟合作博弈,考虑现实局中人的不同偏好信息,通过引入风险偏好均值,提出了具有风险偏好的区间支付交流结构合作博弈及其平均树解.通过公理化体系对此解的存在性进行了证明,并将此分配方法应用到供应链纵向研发合作企业收益分配的实例中,表明该方法的有效性和可行性.此研究同时考虑了合作结盟的限制约束性和局中人的风险态度差异性,不仅能有效刻画现实结盟情境,且利于分配收益函数的求解.     

区间数线性规划问题的解法

基于区间数与实数之间的关系,提出了区间数线性规划的激进最优解,保守最优解的定义.利用约束集之间以及目标函数值之间的关系,在原有区间数线性规划的基础之上,给出了两个求解激进最优解、保守最优解的方法.数值例子验证了该方法的有效性和可行性.     

直觉模糊联盟合作博弈的非线性规划模型

本文研究联盟是直觉模糊集的合作博弈。首先,给出直觉模糊联盟的定义,并根据Choquet积分的直觉模糊形式,得到直觉模糊联盟合作博弈的区间值特征函数,进一步证明直觉模糊联盟合作博弈的区间值特征函数具有超可加性、凸性、弱超可加性. 其次根据区间数的闵可夫斯基距离、区间数的排序及损失函数的定义,建立直觉模糊联盟合作博弈的非线性规划模型,并对其求解得到最优分配. 最后给出一个具体的事例说明本文所建立的模型的合理性和有效性。     

Polytope Games

Starting from the definition of a bimatrix game, we restrict the pair of strategy sets jointly, not independently. Thus, we have a set , which is the set of all feasible strategy pairs. We pose the question of whether a Nash equilibrium exists, in that no player can obtain a higher payoff by deviating. We answer this question affirmatively for a very general case, imposing a minimum of conditions on the restricted sets and the payoff. Next, we concentrate on a special class of restricted games, the polytope bimatrix game, where the restrictions are linear and the payoff functions are bilinear. Further, we show how the polytope bimatrix game is a generalization of the bimatrix game. We give an algorithm for solving such a polytope bimatrix game; finally, we discuss refinements to the equilibrium point concept where we generalize results from the theory of bimatrix games.     

Uncertain bimatrix game with applications

In real-world games, the players are often lack of the information about the other players’ (or even his own) payoffs. Assuming that all entries of payoff matrices are uncertain variables, this paper introduces a concept of uncertain bimatrix game. Within the framework of uncertainty theory, three solution concepts of uncertain equilibrium strategies as well as their existence theorem are proposed. Furthermore, a sufficient and necessary condition is presented for finding the uncertain equilibrium strategies. Finally, an example is provided for illustrating the usefulness of the theory developed in this paper.     

Static search games played over graphs and general metric spaces

We define a general game which forms a basis for modelling situations of static search and concealment over regions with spatial structure. The game involves two players, the searching player and the concealing player, and is played over a metric space. Each player simultaneously chooses to deploy at a point in the space; the searching player receiving a payoff of 1 if his opponent lies within a predetermined radius r of his position, the concealing player receiving a payoff of 1 otherwise. The concepts of dominance and equivalence of strategies are examined in the context of this game, before focusing on the more specific case of the game played over a graph. Methods are presented to simplify the analysis of such games, both by means of the iterated elimination of dominated strategies and through consideration of automorphisms of the graph. Lower and upper bounds on the value of the game are presented and optimal mixed strategies are calculated for games played over a particular family of graphs.     

Alfa-cut based linear programming methodology for constrained matrix games with payoffs of trapezoidal fuzzy numbers

The purpose of this paper is to develop an effective methodology for solving constrained matrix games with payoffs of trapezoidal fuzzy numbers (TrFNs), which are a type of two-person non-cooperative games with payoffs expressed by TrFNs and players’ strategies being constrained. In this methodology, it is proven that any Alfa-constrained matrix game has an interval-type value and hereby any constrained matrix game with payoffs of TrFNs has a TrFN-type value. The auxiliary linear programming models are derived to compute the interval-type value of any Alfa-constrained matrix game and players’ optimal strategies. Thereby the TrFN-type value of any constrained matrix game with payoffs of TrFNs can be directly obtained through solving the derived four linear programming models with data taken from only 1-cut and 0-cut of TrFN-type payoffs. Validity and applicability of the models and method proposed in this paper are demonstrated with a numerical example of the market share game problem.     

Bounded rationality, strategy simplification, and equilibrium

It is frequently suggested that predictions made by game theory could be improved by considering computational restrictions when modeling agents. Under the supposition that players in a game may desire to balance maximization of payoff with minimization of strategy complexity, Rubinstein and co-authors studied forms of Nash equilibrium where strategies are maximally simplified in that no strategy can be further simplified without sacrificing payoff. Inspired by this line of work, we introduce a notion of equilibrium whereby strategies are also maximally simplified, but with respect to a simplification procedure that is more careful in that a player will not simplify if the simplification incents other players to deviate. We study such equilibria in two-player machine games in which players choose finite automata that succinctly represent strategies for repeated games; in this context, we present techniques for establishing that an outcome is at equilibrium and present results on the structure of equilibria.     

A game of optimal pursuit of one object by several

A differential game in which m dynamical objects pursue a single one is investigated. All the players perform simple motions. The termination time of the game is fixed. The controls of the first k (k ⩽ m) pursuers are subject to integral constraints and the controls of the other pursuers and the evader are subject to geometric constraints. The payoff of the game is the distance between the evader and the closest pursuer at the instant the game is over. Optimal strategies for the players are constructed and the value of the game is found.     

Games of timing with resources of mixed type

The paper considers a game of timing which is closely related to the so-called duels. This is a game connected with the distribution of resources by two players. Each of the players is in possession of some amount of resource to be distributed by him in the time interval [0, 1]. In his behavior, Player 1 is restricted by the necessity of taking all of his resources at a single point, while Player 2 has no restrictions. For the payoff function, defined as for duels, the game is solved; explicit formulas on the value of the game and the optimal strategies for the players are found.     

Service rate control of closed Jackson networks from game theoretic perspective

Game theoretic analysis of queueing systems is an important research direction of queueing theory. In this paper, we study the service rate control problem of closed Jackson networks from a game theoretic perspective. The payoff function consists of a holding cost and an operating cost. Each server optimizes its service rate control strategy to maximize its own average payoff. We formulate this problem as a non-cooperative stochastic game with multiple players. By utilizing the problem structure of closed Jackson networks, we derive a difference equation which quantifies the performance difference under any two different strategies. We prove that no matter what strategies the other servers adopt, the best response of a server is to choose its service rates on the boundary. Thus, we can limit the search of equilibrium strategy profiles from a multidimensional continuous polyhedron to the set of its vertex. We further develop an iterative algorithm to find the Nash equilibrium. Moreover, we derive the social optimum of this problem, which is compared with the equilibrium using the price of anarchy. The bounds of the price of anarchy of this problem are also obtained. Finally, simulation experiments are conducted to demonstrate the main idea of this paper.