Machine Learning and the City

Machine Learning and the City

Explore the applications of machine learning and artificial intelligence to the built environment

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:

• An introduction to the probabilistic logic that underpins machine learning
• Comprehensive explorations of the applications of machine learning and artificial intelligence to urban environments
• Practical discussions of the consequences of applied machine learning and the future of urban design

Perfect for designers approaching machine learning and AI for the first time, Machine Learning and the City: Applications in Architecture and Urban Design will also earn a place in the libraries of urban planners and engineers involved in urban design.

Table of Contents

Section I Urban Complexity

1 Urban Complexity

2 Emergence and Universal Computation

3 Fractals and Geography

Project 1 Emergence and Urban Analysis

Project 2 The Evolution and Complexity of Urban St reet Networks

Section II Machines that Think

4 Artificial Intelligence, Logic, and Formalising Common Sense

5 Defining Artificial Intelligence

6 Al: From Copy of Human Brain to Independent Learner

7 The History of Machine Learning and Its Convergent Trajectory Towards Al

8 Machine Behaviour

Project 3 Plan Generation from Program Graph

Project 4 Self-organising Floor Plans in Care Homes

Project 5 N2P2 – Neural Networks and Public Places

Project 6 Urban Fictions

Project 7 Latent Typologies: Architecture in Latent Space

Project 8 Enabling Alternat ive Architectures

Project 9 Distant Readings of Architecture: A Machine View of the City

Section Ill How Machines Learn

9 What Is Machine Learning?

10 Machine Learning: An Applied Mathematics Introduction

11 Machine Learning for Urban Computing

12 Autonomous Artificial Intelligent Agents

Project 10 Machine Learning for Spatial and Visual Connectivity

Project 11 Navigating Indoor Spaces Using Machine Learning: Train Stations in Paris

Project 12 Evolutionary Design Optimisation of Traffic Signals Applied to Quito City

Project 13 Constructing Agency: Self-directed Robotic Environments

Section IV Application to the City

13 Code and the Transduction of Space

14 Augmented Reality in Urban Places: Contested Content and the Duplicity of Code

15 Spatial Data in Urban Informatics: Contentions of the Software-sorted City

16 Urban Morphology Meets Deep Learning: Exploring Urban Forms in One Million Cities, Towns, and Villages Across the Planet

17 Computational Urban Design: Methods and Case Studies

18 lndexical Cities: Personal City Models with Data as Infrastructure

19 Machine Learning, Artificial Intelligence, and Urban Assemblages

20 Making a Smart City Legible

Project 14 A Tale of Many Cities: Universal Patterns in Human Urban Mobility

Project 15 Using Cellular Automata for Parking Recommendations in Smart Environments

Project 16 Gan Hadid

Project 17 Collective Design for Collective Living

Project 18 Architectural Machine Translation

Project 19 Large-scale Evaluation of the Urban Street View with Deep Learning Method

Project 20 Urban Portraits

Project 21 ML-City

Project 22 Imaging Place Using Generative Adversarial Networks (GAN Loci)

Project 23 Urban Forestry Science

Section V Machine Learning and Humans

21 Ten Simple Rules for Responsible Big Data Research

22 A Unified Framework of Five Principles for Al in Society

23 The Big Data Divide and Its Consequences

24 Design Fiction: A Short Essay on Design, Science, Fact, and Fiction

25 Superintelligence and Singularity

Project 25 Emotional Al in Cit ies: Cross-cultural Lessons from the UK and Japan on Designing for an Ethical Life

Project 26 Decoding Urban Inequality: The Applications of Machine Learning for Mapping Inequality in Cit ies of the Global South

Project 27 Amsterdam 2040

Project 28 Committee of Infrastructure

About the Author

Silvio Carta is an architect and Associate Professor at the University of Hertfordshire, UK. His research interests include digital architecture, data-driven approaches and computational design. Silvio is the author of Big Data, Code and the Discrete City. Shaping Public Realms (Routledge 2019).