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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/complexity
课程评论：没有评论
课程名称：复杂性科学导论 课程概述：本课程探讨复杂性科学的特征。我们的世界被众多复杂系统所连接。在从物理、生命到社会的各个层面上，我们可以思考个体元素之间的连接以及它们如何相互作用并影响彼此。例如，人类在群体中传播疫情，车辆在交通系统中的互动，以及网络在政府组织中的连接。尽管这些系统各异，但它们却有着惊人的共同特征。 在过去的几十年中，复杂性科学的研究逐渐增加。广泛认为，创新、综合和分析思维方式对于理解人类社会中的复杂问题至关重要。课程旨在为每个人提供复杂系统的全面介绍，讨论系统的韧性、稳健性和可持续性，并学习复杂系统分析的基本数学方法，例如政权转变和临界点、基于 агент 的建模、动态和网络理论。最重要的是，我们将这些理论应用于城市和健康的实际案例中，帮助学生获得复杂系统思维的实践经验。 课程大纲： - 第一周：复杂系统导论 - 课程概览，解释复杂性科学的演变及其在社会中的应用，强调对复杂系统基本理解的重要性。通过Jupyter Notebook练习，让学生亲身体验模型和方法的实际应用，包括Nagel-Schreckenberg交通模型和生命游戏。 - 第二周：稳健性、韧性与可持续性 - 讨论复杂系统的稳健性、韧性与可持续性的定义，并探讨展示这些特征的案例研究。 - 第三周：政权转变与临界点 - 探索政权转变和临界点及其在预测中的应用。 - 第四周：基于Agent的建模导论 - 介绍基于Agent的建模，包括其定义、工作原理、使用原因及其使用方法，随后进行Schelling的隔离模型的Jupyter Notebook练习。 - 第五周：静态复杂网络导论 - 研究复杂网络及其特征，介绍不同的网络模型，并通过关于复杂网络流行病的Jupyter Notebook练习结束。 本课程通过涵盖多个主题和实践应用，帮助学生建立对复杂性科学的深入理解。
Name:Course Overview and Week 1: Introduction to Complex Systems
Description:An overview of what is covered in the first topic: an introduction to complex systems, explaining how complexity science has evolved, how it has been applied in society, and why it is important to gain a basic understanding of complex systems. Like for all sciences, complexity science is not a spectators' sport. After learning models and methods from the lectures, you will need to try some of these out to develop a practical feel for what they mean and what they can do. This is where the Jupyter Notebook exercises come in. In this course week, we will try out two Jupyter Notebook exercises, on: (1) the Nagel-Schreckenberg model of vehicular traffic, and (2) the Game of Life.
Name:Week 2: Robustness, Resilience, and Sustainability
Description:In this 2nd topic, we look at how robustness, resilience and sustainability can be defined for complex systems, and some case studies that showcase these attributes.
Name:Week 3: Regime Shifts and Tipping Points
Description:In this third topic, we move on to looking at regime shifts and tipping points and their applications in forecasting.
Name:Week 4: Introduction to Agent-Based Modeling
Description:Next, we look at Agent-Based Modeling - what it is, how it works, why it is used and how to use it. We then try a Jupyter Notebook exercise on Schelling’s Segregation Model.
Name:Week 5: Introduction to Static Complex Network
Description:Lastly, we look at complex networks and their attributes before looking at different network models. We end this topic with a Jupyter Notebook exercise on epidemics on complex networks.
This course explores the features of complexity science. Our world is connected by an abundance of complex systems. Across all levels of organizations from physical, biological world to the social world, we may think of the connectivity between individual elements and how they interact and influence each other. For example, how humans transmit pandemics within a group, how cars interact in the traffic system and how networks connect in governmental organizations. Although these systems are diverse and different, they have surprisingly huge features in common. In the past several decades, the study of complexity science has been increasing. It is widely acknowledged that an innovative, integrated and analytical way of thinking is essential for understanding the complex issues in the human societies. In this course, we will aim to give everyone a comprehensive introduction of the complex systems, to talk about the resilience, robustness and sustainability of the systems and to learn basic mathematical methods for complex system analysis, for example regime shifts and tipping points, the agent-based modelling, the dynamic and network theories. Most importantly, we will implement the theories into practical applications of cities and health to help students gain practice in complex systems way of thinking.
