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经济代写|微观经济学代考Microeconomics代写|The satisfaction principle

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经济代写|微观经济学代考Microeconomics代写|The satisfaction principle

经济代写|微观经济学代考Microeconomics代写|The satisfaction principle

The satisfaction principle is the only principle common to both evolutionist and classical game theory. It requires that, in addition to the set of players, the set of strategies available to each of them, one specifies for each player a utility function, which defines his payoff at each issue of the game (which may be repeated). It specifies the set of players, the set of strategies available to each of them as well as his utility function, i. e. his payoff at each issue of the stage game. The opportunities and preferences of the players are supposed to be given (to the modeller) at the beginning of the game and stay unchanged.

The standard illustration, systematically used in the future, is the “technology game”. It represents the coordination problem faced by two firms, 1 and 2 , which have to choose among two technologies, A and $\mathrm{B}$. The technology B, in contrast to the technology A, is a state-of- the-art- tech-nology: both firms, if they both choose B, better perform -they both get 4 than if they both choose A -they both get 2. When one firm uses technology A and the other technology B, the first firm gets $b$ and the second $c$, these parameters being further specified. Note that this game is symmetric whatever the values assigned to $b$ and $c$ (firms A and B have the same strategy set and achieve the same payoffs in symmetric issues). The corresponding game matrix, a symmetric matrix, is the following:

In a first variant of the technology game, looking like Rousseau’s stag hunt game, one states $b=1$ and $c=0$. It means that the inferior technology $\mathrm{A}$, better mastered than technology B, can be used alone (with a reduced payoff). Conversely, the superior technology $\mathrm{B}$, which needs to develop, is bad when used alone. In this variant, the technology $A$ is less risky than technology B, in that it yields a payoff which less depends on the choice of the other firm (the payoff is between 1 and 2 for technology A, in contrast to 0 and 4 for technology B). The corresponding matrix is the following (variant 1):

The stage game may be isolated or part of a bigger game, which is potentially much more complex. A stage game is isolated when the payoffs of the confronted players at a given period are independent of the behavior of all other players, which potentially play the same game, at the present (and preceding) periods. Some degree of isolation is necessary for a game to be studied in an evolutionist way; more precisely, in case of lack of the isolation assumption, it is possible to address the game only if the stage game smoothly changes from one period to the other, due to the evolution of the global game, whose impact is felt only progressively. So the technology game is perhaps not necessarily an isolated game: the prices of both technologies A and B, and therefore the benefits achieved with each of them, may depend on the behavior of other firms having to choose among the technologies A and B (and possibly other technologies), as well as on the behavior of consumers supposed to buy the product produced by means of the different technologies.

经济代写|微观经济学代考Microeconomics代写|The confrontation principle

Players play repeatedly, a finite or infinite number of times, a $n$-player stage game. The stage game is a non cooperative game in the usual sense, in normal or extensive form. The payoffs of the players are aggregated thanks to some discount rate (see chapter 1).

The $n$-player stage game is supposed to be played by $n$ players or, more usually in evolutionist games, by $n$ populations of agents, each agent of the population $i$ playing the role of player i. In each period, several $n$-uplets of individuals are randomly drawn from the $n$ populations (or subsets of these $n$ populations), one agent from each population, and each $n$-uplet of agents plays the game. The interactions may be more or less numerous at each period. On one side, a single $n$-uplet is constituted in a random way. On the other side, all possible $n$-uplets are formed. In the technology game, if each firm is represented by an equal number of agents (each agent having a given technology), each agent of one population may meet one firm of the other population or many combinations can be sorted out.

A usual distinction about meetings concerns the “multi-population” or the “mono-population” approach. The multi-population approach is available for any game and corresponds to differenciated players. Agents from a given population meet agents from the other populations. By contrast, the mono-population approach is reserved to symmetric games when players are considered as interchangeable. Agents form a unique population and meet any agents from that population. For a symmetric game, the two approaches are then available while only the first is available for non symmetric games. For example, one may study the technology game with two populations of agents, namely if the two firms are not located in the same place and if the game can only confront firms not located in a same place, but also with only one population of agents if the firms are interchangeable.

A second distinction about meetings makes a difference between “global interaction” and “local interaction”. In a local interaction model, the agents which an agent may meet in a given period belong to subsets of the other population(s). These subsets figure agent’s local “interaction neighborhood”. For example, in some traditional evolutionist games, agents are located on a one or two dimensional space, like a circle or a torus, and the interaction neighborhood spontaneously includes agents who are physically near them. By contrast, in a global interaction model, each agent may meet any agent in the opponent population(s). Global interaction is just a special case of local interaction (the size of the subsets is the cardinality of the populations). For instance, the technology game may be played by firms situated on a circle and a firm meets only the firms at its right and left.

经济代写|微观经济学代考Microeconomics代写|The satisfaction principle


经济代写|微观经济学代考Microeconomics代写|The satisfaction principle


末来系统地使用的标准揷图是“技术游戏”。它表示两家公司 1 和 2 面临的协调问题,它们必须在两种技术 $A$ 和 B. 与技术 $A$ 相比,技术 $B$ 是最先进的技术: 两家公司,如果他们都选择 $B$ ,则表现更好 – 他们都得到 4 比如 果他们都选择 $A$ – 他们都得 2. 当一家公司使用技术 $A$ 而另一家公司使用技术 $B$ 时,第一家公司得到 $b$ 第二个 $C$ ,这些参数被进一步指定。请注意,无论分配给什么值,这个游戏都是对称的 $b$ 和 $c$ (公司 $\mathrm{A}$ 和 $\mathrm{B}$ 具有相同的策 略集并在对称问题上获得相同的收益) 。对应的博恋矩阵是一个对称矩阵,如下所示:
在技术游戏的第一个变体中,看起来像卢梭的猎鹿游戏,有人说 $b=1$ 和 $c=0$. 就是技术差的意思 $\mathrm{A}$ ,比技术 $B$ 掌握得更好,可以单独使用 (收益减少) 。反之,先进的技术 $B$ ,需要开发,单独使用是不好的。在这个变体 中,技术 $A$ 比技术 $\mathrm{B}$ 风险更小,因为它产生的收益较少取决于另一家公司的选择 (技术 $\mathrm{A}$ 的收益在 1 和 2 之 间,而技术 $B$ 的收益在 0 和 4 之间) 。相应的矩阵如下(变体 1 ) :
舞台游戏可能是孤立的,也可能是更大游戏的一部分,这可能要复杂得多。当在给定时期内对抗参与者的收益 独立于当前 (和之前) 时期可能玩相同游戏的所有其他参与者的行为时,阶段博亦是孤立的。要以进化论的方 式研究游戏,一定程度的隔离是必要的;更准确地说,在缺乏隔离假设的情况下,只有当阶段博亦从一个时期 平稳地变化到另一个时期时,才有可能解快博恋问题,这是由于全球博亦的演变,其影响只能逐渐感受到。因 此,技术游戏可能不一定是孤立的游戏:技术 $A$ 和 $B$ 的价格,以及它们各自带来的收益,

经济代写|微观经济学代考Microeconomics代写|The confrontation principle

玩家重复玩,有限次或无限次,an-玩家阶段游戏。阶段博帟是通常意义上的非合作博恋,其形式 是正常的或广泛的。由于某些贴现率(见第 1 章),参与者的收益被汇总。
这 $n$-玩家阶段游戏应该由 $n$ 玩家,或者更常见的是在进化论游戏中,通过 $n$ 代理人群体,人口中的每 个代理人 $i$ 扮演玩家 $\mathrm{i}$ 的角色。每个时期都有几个 $n-$ 个体的 uplets 是随机抽取的 $n$ 人口(或这些人 口的子集 $n$ 种群),每个种群中的一个代理人,以及每个 $n$-代理人玩游戏。每个时期的相互作用可 能更多或更少。一方面,单 $n$-uplet 以随机方式构成。另一边,一切皆有可能n-形成了连体。在技 术博亦中,如果每个公司由相同数量的代理人 (每个代理人都拥有给定的技术) 代表,则一个群体中 的每个代理人可能会遇到另一个群体中的一个公司,或者可以挑选出许多组合。




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微观经济学是主流经济学的一个分支,研究个人和企业在做出有关稀缺资源分配的决策时的行为以及这些个人和企业之间的相互作用。my-assignmentexpert™ 为您的留学生涯保驾护航 在数学Mathematics作业代写方面已经树立了自己的口碑, 保证靠谱, 高质且原创的数学Mathematics代写服务。我们的专家在图论代写Graph Theory代写方面经验极为丰富,各种图论代写Graph Theory相关的作业也就用不着 说。




现代博弈论始于约翰-冯-诺伊曼(John von Neumann)提出的两人零和博弈中的混合策略均衡的观点及其证明。冯-诺依曼的原始证明使用了关于连续映射到紧凑凸集的布劳威尔定点定理,这成为博弈论和数学经济学的标准方法。在他的论文之后,1944年,他与奥斯卡-莫根斯特恩(Oskar Morgenstern)共同撰写了《游戏和经济行为理论》一书,该书考虑了几个参与者的合作游戏。这本书的第二版提供了预期效用的公理理论,使数理统计学家和经济学家能够处理不确定性下的决策。


微积分,最初被称为无穷小微积分或 “无穷小的微积分”,是对连续变化的数学研究,就像几何学是对形状的研究,而代数是对算术运算的概括研究一样。

它有两个主要分支,微分和积分;微分涉及瞬时变化率和曲线的斜率,而积分涉及数量的累积,以及曲线下或曲线之间的面积。这两个分支通过微积分的基本定理相互联系,它们利用了无限序列和无限级数收敛到一个明确定义的极限的基本概念 。





MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中,其中问题和解决方案以熟悉的数学符号表示。典型用途包括:数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发,包括图形用户界面构建MATLAB 是一个交互式系统,其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题,尤其是那些具有矩阵和向量公式的问题,而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问,这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展,得到了许多用户的投入。在大学环境中,它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域,MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要,工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数(M 文件)的综合集合,可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

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