SS01 – Machine Learning for Urban Futures

This engineering project explores the potential of integrating machine learning into Cities: Skylines to gain insights into urban planning strategies. By implementing AI-driven infrastructure development and management in the virtual environment, the project aims to analyze diverse urban planning approaches and their impacts on factors like growth, efficiency, and livability. The simulation-based methodology allows for the testing and evaluation of a wide range of infrastructure building techniques, with the goal of uncovering optimal urban planning solutions that could be applied in real-world settings. The insights gained from this project have the potential to benefit government entities, urban planners, and the general public. The simulation-derived data and analysis could inform policymaking and infrastructure development decisions by providing data-driven guidance. Furthermore, this project could advance the use of machine learning in urban planning, leading to the creation of more accurate predictive models and decision support tools. Additionally, the identification of planning strategies that enhance the quality of life for citizens could promote the development of sustainable, resilient, and equitable cities. By leveraging the power of simulation and machine learning, this project bridges the gap between virtual and real-world urban planning, ultimately contributing to the creation of more livable and thriving cities.