Machine Learning and the City

Applications in Architecture and Urban Design

Häftad, Engelska, 2022

Av Silvio Carta, Silvio Carta, UK) Carta, Silvio (University of Hertfordshire

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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 learningComprehensive explorations of the applications of machine learning and artificial intelligence to urban environmentsPractical discussions of the consequences of applied machine learning and the future of urban designPerfect 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.

Produktinformation

Utgivningsdatum2022-06-09
Mått170 x 244 x 37 mm
Vikt1 134 g
FormatHäftad
SpråkEngelska
Antal sidor672
FörlagJohn Wiley and Sons Ltd
ISBN9781119749639

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Arkitektur inom Kultur

Preface xiiiAcknowledgements xvIntroduction xviSection I Urban Complexity 11 Urban Complexity 3Sean Hanna2 Emergence and Universal Computation 15Cassey Lee3 Fractals and Geography 31Pierre Frankhauser and Denise PumainProject 1 Emergence and Urban Analysis 57Ljubomir JankovicProject 2 The Evolution and Complexity of Urban Street Networks 63Nahid Mohajeri and Agust GudmundssonSection II Machines that Think 694 Artificial Intelligence, Logic, and Formalising Common Sense 71John McCarthy5 Defining Artificial Intelligence 91David B. Fogel6 AI: From Copy of Human Brain to Independent Learner 121Shelly Fan7 The History of Machine Learning and Its Convergent Trajectory Towards AI 129Keith D. Foote8 Machine Behaviour 143Iyad Rahwan, Manuel Cebrian, Nick Obradovich, Josh Bongard, Jean-François Bonnefon, Cynthia Breazeal, Jacob W. Crandall, Nicholas A. Christakis, Iain D. Couzin, Matthew O. Jackson, Nicholas R. Jennings, Ece Kamar, Isabel M. Kloumann, Hugo Larochelle, David Lazer, Richard McElreath, Alan Mislove, David C. Parkes, Alex ‘Sandy’ Pentland, Margaret E. Roberts, Azim Shariff, Joshua B. Tenenbaum, and Michael WellmanProject 3 Plan Generation from Program Graph 167Ao Li, Runjia Tian, Xiaoshi Wang, and Yueheng LuProject 4 Self-organising Floor Plans in Care Homes 171Silvio Carta, Stephanie St. Loe, Tommaso Turchi, and Joel SimonProject 5 N2P2 – Neural Networks and Public Places 177Roberto Bottazzi, Tasos Varoudis, Piyush Prajapati, and Xi WangProject 6 Urban Fictions 183Matias del Campo, Sandra Manninger, and Alexandra CarlsonProject 7 Latent Typologies: Architecture in Latent Space 189Stanislas ChaillouProject 8 Enabling Alternative Architectures 193Nate PetersProject 9 Distant Readings of Architecture: A Machine View of the City 201Andrew WittSection III How Machines Learn 2079 What Is Machine Learning? 209Jason Bell10 Machine Learning: An Applied Mathematics Introduction 217Paul Wilmott11 Machine Learning for Urban Computing 249Bilgeçağ Aydoğdu and Albert Ali Salah12 Autonomous Artificial Intelligent Agents 263Iaroslav OmelianenkoProject 10 Machine Learning for Spatial and Visual Connectivity 287Sherif Tarabishy, Stamatios Psarras, Marcin Kosicki, and Martha TsigkariProject 11 Navigating Indoor Spaces Using Machine Learning: Train Stations in Paris 293Zhoutong Wang, Qianhui Liang, Fabio Duarte, Fan Zhang, Louis Charron, Lenna Johnsen, Bill Cai, and Carlo RattiProject 12 Evolutionary Design Optimisation of Traffic Signals Applied to Quito City 297Rolando Armas, Hernán Aguirre, Fabio Daolio, and Kiyoshi TanakaProject 13 Constructing Agency: Self-directed Robotic Environments 303Patrik SchumacherSection IV Application to the City 30913 Code and the Transduction of Space 311Martin Dodge and Rob Kitchin14 Augmented Reality in Urban Places: Contested Content and the Duplicity of Code 341Mark Graham, Matthew Zook, and Andrew Boulton15 Spatial Data in Urban Informatics: Contentions of the Software-sorted City 367Marcus Foth, Fahame Emamjome, Peta Mitchell, and Markus Rittenbruch16 Urban Morphology Meets Deep Learning: Exploring Urban Forms in One Million Cities, Towns, and Villages Across the Planet 379Vahid Moosavi17 Computational Urban Design: Methods and Case Studies 393Snoweria Zhang and Luc Wilson18 Indexical Cities: Personal City Models with Data as Infrastructure 409Diana Alvarez-Marin19 Machine Learning, Artificial Intelligence, and Urban Assemblages 445Serjoscha Düring, Reinhard Koenig, Nariddh Khean, Diellza Elshani, Theodoros Galanos, and Angelos Chronis20 Making a Smart City Legible 453Franziska Pilling, Haider Ali Akmal, Joseph Lindley, and Paul CoultonProject 14 A Tale of Many Cities: Universal Patterns in Human Urban Mobility 467Anastasios Noulas, Salvatore Scellato, Renaud Lambiotte, Massimiliano Pontil, and Cecilia MascoloProject 15 Using Cellular Automata for Parking Recommendations in Smart Environments 473Gwo-Jiun HorngProject 16 Gan Hadid 477Sean WallishProject 17 Collective Design for Collective Living 483Elizabeth Christoforetti and Romy El SayahProject 18 Architectural Machine Translation 489Erik SwahnProject 19 Large-scale Evaluation of the Urban Street View with Deep Learning Method 495Hui Wang, Elisabete A. Silva, and Lun LiuProject 20 Urban Portraits 501Jose Luis García del Castillo y LópezProject 21 ML-City 507Benjamin EnnemoserProject 22 Imaging Place Using Generative Adversarial Networks (GAN Loci) 513Kyle SteinfeldProject 23 Urban Forestry Science 517Iacopo TestiSection V Machine Learning and Humans 52121 Ten Simple Rules for Responsible Big Data Research 523Matthew Zook, Solon Barocas, Danah Boyd, Kate Crawford, Emily Keller, Seeta Peña Gangadharan, Alyssa Goodman, Rachelle Hollander, Barbara A. Koenig, Jacob Metcalf, Arvind Narayanan, Alondra Nelson, and Frank Pasquale22 A Unified Framework of Five Principles for AI in Society 535Luciano Floridi and Josh Cowls23 The Big Data Divide and Its Consequences 547Matthew T. McCarthy24 Design Fiction: A Short Essay on Design, Science, Fact, and Fiction 561Julian Bleecker25 Superintelligence and Singularity 579Ray Kurzweil26 The Social Life of Robots: The Politics of Algorithms, Governance, and Sovereignty 603Vincent J. Del Casino Jr, Lily House-Peters, Jeremy W. Crampton, and Hannes GerhardtProject 24 Experiments in Synthetic Data 615Forensic ArchitectureProject 25 Emotional AI in Cities: Cross-cultural Lessons from the UK and Japan on Designing for an Ethical Life 621Vian Bakir, Nader Ghotbi, Tung Manh Ho, Alexander Laffer, Peter Mantello, Andrew McStay, Diana Miranda, Hiroshi Miyashita, Lena Podoletz, Hiromi Tanaka, and Lachlan UrquhartProject 26 Decoding Urban Inequality: The Applications of Machine Learning for Mapping Inequality in Cities of the Global South 625Kadeem KhanProject 27 Amsterdam 2040 631Maria Luce LupettiProject 28 Committee of Infrastructure 635Jason Shun WongIndex 639