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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
• Advanced Probability Theory 高等概率论
• Advanced Mathematical Statistics 高等数理统计学
• (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|Parent–Offspring Conflict

Interactions between parents and offspring involve such issues as how much parents should invest in a given clutch of offspring compared with future clutches, and how the investment in a clutch should be distributed among the individual offspring. Offspring begging for food is a kind of negotiation between offspring and parents, and between the offspring. Here we study a simpler situation, where parents provide a fixed amount of resources to a clutch, and the question is how this amount is distributed among the offspring. We will compare the case where one chick (the oldest) is dominant and can decide on the proportion $p$ of resources to itself with the case where a parent decides the proportions. In many species of birds, the chicks in a clutch compete intensely over food and the oldest chick often dominates its younger siblings (Mock et al., 1990).
Inspired by Parker et al. (1989), we examine the simplest possible situation in which a clutch consists of two siblings, with the older chick being dominant. We assume that the survival to adulthood of a chick that gets a proportion $p$ of the parental resources is
$$s(p)=1-\exp \left(-a\left(p-p_{\min }\right)\right)$$
for $p \geq p_{\min }$ and zero otherwise. The parameter $a$ is related to the total amount of resources invested and $p_{\min }$ is the smallest proportion required for a chick to have a chance to survive. If the dominant chick gets the proportion $p$ with survival $s(p)$, the other chick will get $1-p$ with survival $s(1-p)$. In panel (a) of Fig. $4.10$ we illustrate this chick survival function, together with the evolutionarily stable allocations if they are determined by the dominant chick (dashed lines) or by a parent (dotted line).
Figure 4.10b shows a great egret parent with chicks. Sibling competition is fierce in these birds (Mock et al., 1990), but their breeding characteristics do not agree in detail with our model here. In great egrets the observation is that the parents do not interfere in sibling fights.

To derive the allocations illustrated in Fig. 4.10, we assume that individuals are diploid. For each of the two cases of dominant chick control and parental control, we examine the payoff (proportional to invasion fitness) of a rare mutant $p$ in a resident population using $q$. When the mutant is rare, it occurs overwhelmingly as an allele in a heterozygote genotype. Furthermore, at most one of the mother and the father of a clutch is a mutant heterozygote. As a simplification, we assume that generations are non-overlapping. For each of the two cases, we look for the change from one generation to the next of the frequency of the mutant (gene-centred approach). We can then use as payoff the expected number of adult mutant offspring per breeding attempt (clutch) where one of the parents is a mutant.

经济代写|博弈论代写Game Theory代考|Learning in Large Worlds

Many things that are important for individuals are variable. Among the examples are properties of an individual and its social partners, such as size, strength, and similar qualities, and characteristics of the environment, such as the availability of resources. Individuals might then need to learn about their particular circumstances, rather than relying on innate precepts. For game theory there are two major ways to conceptualize such learning. The first is to assume that individuals have innate representations of the probability distributions of variable features and use experiences to update the priors to adequate posteriors (cf. Section 3.12). We refer to this widely used Bayesian perspective as a ‘small-worlds’ approach. It presupposes that individuals have innate representations of the states of the world, over which prior distributions are defined, as well as representations of the state dynamics. For this to be reasonable the number of states should in some sense be small. The second way is to assume that individuals have much more limited innate precepts, for instance only about what should be sought and what should be avoided, perhaps guided by emotions like pleasure and pain. This can be referred to as a ‘large-worlds’ approach. It may give rise to seemingly adaptive behaviour also in situations where an individual does not have an innate model of the world, for instance because the world, including the decision-making machinery of social partners, is too complex. One can use the term model-free learning to refer to this approach.

An advantage of the large-worlds perspective is that it can be combined with investigation of the properties of model-free learning that are evolutionarily favoured in particular situations. We can for instance study the evolution of an individual’s initial, unlearned tendencies to perform actions, how much the individual pays attention to different classes of stimuli, and the magnitude of the primary rewards that guide learning. As we illustrate in this and later chapters, the approach can be helpful as a method of analysis also for situations (games) that individuals encounter on a day-to-day basis, while living and interacting in social groups.

经济代写|博弈论代写Game Theory代考|Parent–Offspring Conflict

$$s(p)=1-\exp \left(-a\left(p-p_{\min }\right)\right)$$

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