With a focus on the applications in the built environment, Machine Learning, Artificial Intelligence and Urban Assemblages provides the insight needed to understand the application of ML in architecture and the design of cities. Readers will be able to understand the ideas and techniques underpinning ML and then to start using ML techniques in their work, confident in their understanding of the statistical models and logic used, and of the impact of ML and AI on contemporary and future cities. Organised in six sections to take the reader from the origins of machine learning, the book covers the probabilistic logic that underpins ML, it’s application to the city, the consequences of applied ML and the future of urban design. Each section couples theoretical and technical chapters written by key scholars in their field with concrete examples and projects illustrating the power of ML. Each section will provide authoritative references and a direct link to their application to the urban context. Machine Learning, Artificial Intelligence and Urban Assemblages is aimed primarily at those designers who are approaching ML and AI in order to start using it in their work, to enable them to understand the use of ML approaches and the possible design results in a spatial and societal context.
