Machine Learning and the City: Applications in Architecture and Urban Design delivers a robust exploration of machine learning (ML) and artificial intelligence (AI) in the context of the built environment. Relevant contributions from leading scholars in their respective fields describe the ideas and techniques that underpin ML and AI, how to begin using ML and AI in urban design, and the likely impact of ML and AI on the future of city design and planning.
Each section couples theoretical and technical chapters, authoritative references, and concrete examples and projects that illustrate the efficacy and power of machine learning in urban design. The book also includes:
My humble contribution to the book is Chapter 12: Autonomous Artificial Intelligent Agents. In this chapter, I’m illustrating how genetic algorithms, and NEAT (neuroevolution of augmented topologies) in particular, can be used to evolve intelligent agents that can become the foundational building blocks of modern smart city infrastructure.
The book is now awailable at: