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assignmentutor-lab™ 为您的留学生涯保驾护航 在代写博弈论Game Theory方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写博弈论Game Theory代写方面经验极为丰富，各种代写博弈论Game Theory相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 经济代写|博弈论代写Game Theory代考|The Parental Effort Game

Biparental care of young (that is care of young by both the mother and father) is common in birds and is also found in other taxa. For example, in mammals it is found in several primate and rodent species, but is also found in some arthropod species such as burying beetles. When both parents care, how much effort do we predict each parent to invest in care? Survival of the young is a common benefit to both parents, and the more effort expended by a parent the greater the young’s survival prospects. But care also incurs costs. Increased effort by a parent may reduce their opportunities for extra-pair matings. For each parent, in foraging to provision the young the parent may expose itself to increased predation risk and this risk is liable to increase at an accelerating rate with the amount of food delivered to the young. Increased provisioning effort may also reduce the probability that the parent survives the following winter (Daan et al., 1996).

The situation thus involves contributing to a common benefit at individual cost, but now there is a role asymmetry; one parent is in the female role and the other in the male role. To analyse evolutionarily stable levels of effort we regard a strategy as specifying a pair of efforts: the effort if female and the effort if male. Here we are envisaging the genes that control effort to be present in both males and females, but in determining effort they interact with the sex of the individual, so that different sexes can expend different efforts-in fact we will assume there is complete flexibility at no cost in this regard. Suppose the resident population strategy is $(x, y)$, i.e. resident females expend effort $x$ and resident males expend effort $y$. Consider a mutant strategy $\left(x^{\prime}, y^{\prime}\right)$. Then a mutant female expending effort $x^{\prime}$ is typically paired with a resident male who expends effort $y$. The payoff to the female might then be written as $W_{f}\left(x^{\prime}, y\right)=B\left(x^{\prime}+y\right)-C_{f}\left(x^{\prime}\right)$, where $B\left(x^{\prime}+y\right)$ is the female’s benefit from the survival of the young and $C_{f}\left(x^{\prime}\right)$ is the cost paid by the female. Similarly the payoff to a mutant male might be written as $W_{m}\left(x, y^{\prime}\right)=B\left(x+y^{\prime}\right)-C_{m}\left(y^{\prime}\right)$. These are referred to as ‘local’ payoffs, because they apply to one of the roles in the game.

## 经济代写|博弈论代写Game Theory代考|Parents Can Respond to Each Other

The above parental effort game is widely used and has an appealing simplicity: at evolutionary stability the effort of each parent is the best given the effort of the other. However, the model has a crucial assumption: parents do not observe one another and adjust their efforts accordingly; rather, their efforts are fixed, genetically determined quantities. This is biologically unrealistic as parents are known to respond to the behaviour of their partner (see, e.g. table 4 in Sanz et al., 2000), although this may be an indirect effect as they may be responding directly to the state of the young, which in turn is influenced by the provisioning rate of their partner. So do models that capture behavioural interactions make different predictions? At a conceptual level, once behavioural responses are allowed, so that parents negotiate effort by each adjusting their own effort in response to the behaviour of their partner, the picture completely changes. Now it is the rules for negotiation with a partner that are genetically determined rather than efforts. At evolutionary stability the negotiation rule of males is the best given that of females, and vice versa. The efforts that are (McNamara et al., 1999b). A basic reason for considering negotiation or similar processes where partners adjust their efforts is that individuals vary, for instance, in their ability and thus cost of providing care. It is an important task for game theory to throw light on such phenomena, but it is also a challenging task as the current behaviour of one individual during the negotiation could potentially depend on the individual’s ability as well as any aspect of the previous behaviour of the two individuals.

Allowing negotiation may or may not produce more cooperative outcomes (McNamara et al., 1999b). This shows that the interaction process can significantly affect outcomes, a theme we return to in Chapter 8. However, in contrast to the approach taken by Roughgarden et al. (2006), cooperation should not be assumed (McNamara et al., 2006a; Binmore, 2010), rather it may or may not emerge as a result of individuals doing the best for themselves and their kin. Genes are selfish in the sense of Dawkins (1976), but this does not imply they code for behaviour that is ‘selfish’ in the sense that is usually used to describe human behaviour.

## 有限元方法代写

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## MATLAB代写

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。

assignmentutor™您的专属作业导师
assignmentutor™您的专属作业导师