### 统计代写 | Statistical Learning and Decision Making代考| Distributed Wildfire Surveillance

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|Distributed Wildfire Surveillance

Situational awareness is a major challenge when fighting wildfires. The state of the fire evolves over time, influenced by factors such as wind and the distribution of fuel in the environment. Many wildfires span large geographic regions. One concept for monitoring a wildfire is to use a team of drones equipped with sensors to fly above the fire. 7 The sensing range of individual drones are limited, but the information from the team can be fused to provide a unified snapshot of the situation to inform resource allocation decisions. We would like the team to autonomously determine how to collaborate with each other to provide the best coverage of the fire. Effective monitoring requires deciding how to maneuver to cover areas where new sensor information is likely to be useful; spending time in areas where we are certain the fire is burning or not would be uninformative. Identifying important areas to explore requires reasoning about the stochastic evolution of the fire given only imperfect knowledge of its current state.

## 统计代写 | Statistical Learning and Decision Making代考|Mars Science Exploration

Rovers have made important discoveries and increased our understanding of Mars. However, a major bottleneck in scientific exploration has been the communication link between the rover and the operations team on Earth. It can take on the order of half an hour for sensor information to be sent from Mars to Earth and for commands to be sent from Earth to Mars. In addition, guidance to rovers need to be planned out in advance because there are limited upload and download windows with Mars due to the positions of orbiters serving as information relays between the planets. Recent research has suggested that the efficiency of science exploration missions can be improved by a factor of five through the introduction of greater levels of autonomy.” Human operators would still provide high-level guidance on mission objectives, but the rover would have the flexibility to select its own science targets using its most up-to-date information. In addition, it would be desirable for rovers to respond appropriately to various hazards and system failures without human intervention.

There are many different methods for designing decision-making agents. Depending on the application, some may be more appropriate than others. They differ in the responsibilities of the designer and the tasks left to automation. This section briefly overviews a collection of these methods. The book will focus primarily on planning and reinforcement learning, but some of the techniques will involve elements of supervised learning and optimization.

The most direct method for designing a decision-making agent is to anticipate all scenarios the agent might find itself in and explicitly program what the agent should do in each one. The explicit programming approach may work well for simple problems, but it places a large burden on the designer to provide a complete strategy. Various agent programming languages and frameworks have been proposed to make programming agents easier.

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

In some problems, it may be easier to show an agent what to do rather than to write a program for the agent to follow. The designer provides a set of training examples, and an automated learning algorithm must generalize from these examples. This approach is known as supervised learning and has been widely applied to classification problems. This technique is sometimes called behavioral cloning when applied to learning mappings from ohservations to actions. Rehavioral cloning works well when an expert designer actually knows the best course of action for a representative collection of example situations. Although there exists a wide variety of different learning algorithms, they generally cannot perform better than human designers in new situations.

Another approach is for the designer to specify the space of possible decision strategies and a performance measure to be maximized. Evaluating the performance of a decision strategy generally involves running a batch of simulations. The optimization algorithm then performs a search in this space for the optimal strategy. If the space is relatively small and the performance measure does not have many local optima, then various local or global search methods may be appropriate. Although knowledge of a dynamic model is generally assumed in order to run the simulations, it is not otherwise used to guide the search, which can be important in complex problems.

Planning is a form of optimization that uses a model of the problem dynamics to help guide the search. A broad base of literature explores various planning problems, much of it focused on deterministic problems. For some problems, it may be acceptable to approximate the dynamics with a deterministic model. Assuming a deterministic model allows us to use methods that can more easily scale to high-dimensional problems. For other problems, accounting for futurc uncertainty is absolutely critical. This book focuses entirely on problems in which accounting for uncertainty is important.

## 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。