### 统计代写 | Statistical Learning and Decision Making代考|Acknowledgments

statistics-lab™ 为您的留学生涯保驾护航 在代写Statistical Learning and Decision Making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Statistical Learning and Decision Making代写方面经验极为丰富，各种代写Statistical Learning and Decision Making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

## 统计代写 | Statistical Learning and Decision Making代考|Decision Making

An agent is an entity that acts based on observations of its environment. Agents may be physical entities, like humans or robots, or they may be nonphysical entities, such as decision support systems that are implemented entirely in software. As shown in figure 1.1, the interaction between the agent and the environment follows an observe-act cycle or loop.

The agent at time $t$ receives an obseroation of the environment, denoted $o_{l}$. Observations may be made, for example, through a biological sensory process as in humans or by a sensor system like radar in an air traffic control system. Observations are often incomplete or noisy; humans may not see an approaching aircraft and a radar system might miss a detection through electromagnetic interference. The agent then chooses an action $a_{t}$ through some decision-making

process. This action, such as sounding an alert, may have a nondeterministic effect on the environment.

Our focus is on agents that interact intelligently to achieve their objectives over time. Given the past sequence of observations $o_{1}, \ldots, o_{l}$ and knowledge about the environment, the agent must choose an action $a_{\ell}$ that best achieves its objectives in the presence of various sources of uncertainty, ${ }^{1}$ including:

1. outcome uncertainty, where the effects of our actions are uncertain,
2. model uncertainty, where our model of the problem is uncertain,
3. state uncertainty, where the true state of the environment is uncertain, and
4. interaction uncertainty, where the behavior of the other agents interacting in the environment is uncertain.

This book is organized around these four sources of uncertainty. Making decisions in the presence of uncertainty is central to the field of artificial intelligence ${ }^{2}$ as well as many other fields, as outlined in section 1.4. We will discuss a variety of algorithms, or descriptions of computational processes, for making decisions that are robust to uncertainty.

## 统计代写 | Statistical Learning and Decision Making代考|Applications

The decision making framework presented in the previous section can be applied to a wide variety of domains. This section discusses a few conceptual examples with real-world applications. Appendix F outlines additional notional examples that are used throughout this text to demonstrate the algorithms we discuss.

To help prevent mid-air collisions between aircraft, we want to design a system that can alert pilots to potential threats and direct them how to maneuver. ${ }^{3}$ The system communicates with the transponders of other aircraft to identify their positions with some degree of accuracy. Deciding what guidance to provide to the pilots from this information is challenging. There is uncertainty in how quickly the pilots will respond and how strongly they will comply with the guidance. In addition, there is uncertainty in the behavior of other aircraft in the vicinity. We want our system to alert sufficiently early to provide enough time for the pilots to maneuver the aircraft to avoid collision, but we do not want our system to alert too early and result in many unnecessary maneuvers. Since this system is to be used continuously worldwide, we need the system to provide an exceptional level of saftety.

## 统计代写 | Statistical Learning and Decision Making代考|Automated Driving

We want to build an autonomous vehicle that can safely drive in urban environments. 4 The vehicle must rely on a suite of sensors to perceive its environment to make safe decisions. One type of sensor is lidar, which involves measuring laser reflections off of the environment to determine distances to obstacles. Another type of sensor is a camera, which, through computer vision algorithms, can detect pedestrians and other vehicles. Both of these types of sensors are imperfect and susceptible to noise and occlusions. For example, a parked truck may occlude a pedestrian that may be trying to cross at a crosswalk. Our system must predict the intentions and future paths of other vehicles, pedestrians, and other road users from their observable behavior in order to safely navigate to our destination.

Worldwide, breast cancer is the most common cancer in women. Detecting breast cancer early can help save lives, with mammography being the most effective screening tool available. However, mammography carries with it potential risks, including false positives, which can result in unnecessary and invasive diagnostic followup. Research over the years has resulted in various population-based screening schedules based on age in order to balance testing benefits and risks. Developing a system that can make recommendations based on personal risk characteristics and screening history has the potential to result in better health outcomes. 5 The success of such a system can be compared to population-wide screening schedules in terms of total expected quality-adjusted life years, the number of mammograms, false-positives, and risk of undetected invasive cancer.

## 统计代写 | Statistical Learning and Decision Making代考|Decision Making

1. 结果不确定性，我们行动的影响是不确定的，
2. 模型不确定性，我们的问题模型不确定，
3. 状态不确定性，即环境的真实状态是不确定的，以及
4. 交互不确定性，其中在环境中交互的其他代理的行为是不确定的。

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## 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。