Explore the realm of computational social science in the "Computer Simulations" course. Discover how computer simulations are used to delve into the theoretical possibilities of societal structures and dynamics. Through hands-on experience, learn to utilize agent-based models to study and design artificial societies. Gain insights into combining hypothetical models with real-world data, and program a simple artificial society from scratch.
With a focus on practical models and real-world applications, you will delve into the complexities of social system design and the ease with which computational tools enable such endeavors. By the end of this course, you will have a comprehensive understanding of how computer simulations contribute to shaping a better world.
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This course delves into the theoretical and practical aspects of computer simulations, covering topics such as theoretical simulations, artificial societies, characteristics of agent-based models, and model thinking and coding.
Explore the theoretical foundations and practical applications of computer simulations. Delve into the concepts of theoretical simulations, modeling, mapping, agent-based models (ABM), and more. Gain hands-on experience in understanding and creating computational models to study societal structures and dynamics.
Get introduced to artificial societies and delve into the complexities of modeling and studying them. Learn about Sugarscape and its various components, including inequality, sex, inheritance, and societal pressures. Gain insights into building and managing artificial societies and how these models reflect real-world scenarios.
Understand the characteristics of agent-based models and their role in computer simulations. Explore CSS for making choices, code implementation, risk assessment, and agent-based emergence. Gain a comprehensive understanding of how these characteristics contribute to the development and analysis of artificial societies.
Delve into model thinking and coding artificial societies, exploring various model outcomes, analytical and numerical concepts, and the application of agent-based models in social epidemiology. Gain hands-on experience in coding and analyzing artificial societies, and explore the complexities of creating and managing these computational models.
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