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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.
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.
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).
Preface xiii
Acknowledgements xv
Introduction xvi
Section I Urban Complexity 1
1 Urban Complexity 3
Sean Hanna
2 Emergence and Universal Computation 15
Cassey Lee
3 Fractals and Geography 31
Pierre Frankhauser and Denise Pumain
Project 1 Emergence and Urban Analysis 57
Ljubomir Jankovic
Project 2 The Evolution and Complexity of Urban Street Networks 63
Nahid Mohajeri and Agust Gudmundsson
Section II Machines that Think 69
4 Artificial Intelligence, Logic, and Formalising Common Sense 71
John McCarthy
5 Defining Artificial Intelligence 91
David B. Fogel
6 AI: From Copy of Human Brain to Independent Learner 121
Shelly Fan
7 The History of Machine Learning and Its Convergent Trajectory Towards AI 129
Keith D. Foote
8 Machine Behaviour 143
Iyad 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 Wellman
Project 3 Plan Generation from Program Graph 167
Ao Li, Runjia Tian, Xiaoshi Wang, and Yueheng Lu
Project 4 Self-organising Floor Plans in Care Homes 171
Silvio Carta, Stephanie St. Loe, Tommaso Turchi, and Joel Simon
Project 5 N2P2 - Neural Networks and Public Places 177
Roberto Bottazzi, Tasos Varoudis, Piyush Prajapati, and Xi Wang
Project 6 Urban Fictions 183
Matias del Campo, Sandra Manninger, and Alexandra Carlson
Project 7 Latent Typologies: Architecture in Latent Space 189
Stanislas Chaillou
Project 8 Enabling Alternative Architectures 193
Nate Peters
Project 9 Distant Readings of Architecture: A Machine View of the City 201
Andrew Witt
Section III How Machines Learn 207
9 What Is Machine Learning? 209
Jason Bell
10 Machine Learning: An Applied Mathematics Introduction 217
Paul Wilmott
11 Machine Learning for Urban Computing 249
Bilgeçä Aydo¿du and Albert Ali Salah
12 Autonomous Artificial Intelligent Agents 263
Iaroslav Omelianenko
Project 10 Machine Learning for Spatial and Visual Connectivity 287
Sherif Tarabishy, Stamatios Psarras, Marcin Kosicki, and Martha Tsigkari
Project 11 Navigating Indoor Spaces Using Machine Learning: Train Stations in Paris 293
Zhoutong Wang, Qianhui Liang, Fabio Duarte, Fan Zhang, Louis Charron, Lenna Johnsen, Bill Cai, and Carlo Ratti
Project 12 Evolutionary Design Optimisation of Traffic Signals Applied to Quito City 297
Rolando Armas, Hernán Aguirre, Fabio Daolio, and Kiyoshi Tanaka
Project 13 Constructing Agency: Self-directed Robotic Environments 303
Patrik Schumacher
Section IV Application to the City 309
13 Code and the Transduction of Space 311
Martin Dodge and Rob Kitchin
14 Augmented Reality in Urban Places: Contested Content and the Duplicity of Code 341
Mark Graham, Matthew Zook, and Andrew Boulton
15 Spatial Data in Urban Informatics: Contentions of the Software-sorted City 367
Marcus Foth, Fahame Emamjome, Peta Mitchell, and Markus Rittenbruch
16 Urban Morphology Meets Deep Learning: Exploring Urban Forms in One Million Cities, Towns, and Villages Across the Planet 379
Vahid Moosavi
17 Computational Urban Design: Methods and Case Studies 393
Snoweria Zhang and Luc Wilson
18 Indexical Cities: Personal City Models with Data as Infrastructure 409
Diana Alvarez-Marin
19 Machine Learning, Artificial Intelligence, and Urban Assemblages 445
Serjoscha Düring, Reinhard Koenig, Nariddh Khean, Diellza Elshani, Theodoros Galanos, and Angelos Chronis
20 Making a Smart City Legible 453
Franziska Pilling, Haider Ali Akmal, Joseph Lindley, and Paul Coulton
Project 14 A Tale of Many Cities: Universal Patterns in Human Urban Mobility 467
Anastasios Noulas, Salvatore Scellato, Renaud Lambiotte, Massimiliano Pontil, and Cecilia Mascolo
Project 15 Using Cellular Automata for Parking Recommendations in Smart Environments 473
Gwo-Jiun Horng
Project 16 Gan Hadid 477
Sean Wallish
Project 17 Collective Design for Collective Living 483
Elizabeth Christoforetti and Romy El Sayah
Project 18 Architectural Machine Translation 489
Erik Swahn
Project 19 Large-scale Evaluation of the Urban Street View with Deep Learning Method 495
Hui Wang, Elisabete A. Silva, and Lun Liu
Project 20 Urban Portraits 501
Jose Luis García del Castillo y López
Project 21 ML-City 507
Benjamin Ennemoser
Project 22 Imaging Place Using Generative Adversarial Networks (GAN Loci) 513
Kyle Steinfeld
Project 23 Urban Forestry Science 517
Iacopo Testi
Section V Machine Learning and Humans 521
21 Ten Simple Rules for Responsible Big Data Research 523
Matthew 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 Pasquale
22 A Unified Framework of Five Principles for AI in Society 535
Luciano Floridi and Josh Cowls
23 The Big Data Divide and Its Consequences 547
Matthew T. McCarthy
24 Design Fiction: A Short Essay on Design, Science, Fact, and Fiction 561
Julian Bleecker
25 Superintelligence and Singularity 579
Ray Kurzweil
26 The Social Life of Robots: The Politics of Algorithms, Governance, and Sovereignty 603
Vincent J. Del Casino Jr, Lily House-Peters, Jeremy W. Crampton, and Hannes Gerhardt
Project 24 Experiments in Synthetic Data 615
Forensic Architecture
Project 25 Emotional AI in Cities: Cross-cultural Lessons from the UK and Japan on Designing for an Ethical Life 621
Vian Bakir, Nader Ghotbi, Tung Manh Ho, Alexander Laffer, Peter Mantello, Andrew McStay, Diana Miranda, Hiroshi Miyashita, Lena Podoletz, Hiromi Tanaka, and Lachlan Urquhart
Project 26 Decoding Urban Inequality: The Applications of Machine Learning for Mapping Inequality in Cities of the Global South 625
Kadeem Khan
Project 27 Amsterdam 2040 631
Maria Luce Lupetti
Project 28 Committee of Infrastructure 635
Jason Shun Wong
Index 639
| Erscheinungsjahr: | 2022 |
|---|---|
| Genre: | Kunst |
| Rubrik: | Kunst & Musik |
| Thema: | Architektur |
| Medium: | Taschenbuch |
| Inhalt: | 672 S. |
| ISBN-13: | 9781119749639 |
| ISBN-10: | 1119749638 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Carta, Silvio |
| Redaktion: | Carta, Silvio |
| Herausgeber: | Silvio Carta |
| Hersteller: | Wiley |
| Maße: | 244 x 170 x 36 mm |
| Von/Mit: | Silvio Carta |
| Erscheinungsdatum: | 17.05.2022 |
| Gewicht: | 1,143 kg |
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).
Preface xiii
Acknowledgements xv
Introduction xvi
Section I Urban Complexity 1
1 Urban Complexity 3
Sean Hanna
2 Emergence and Universal Computation 15
Cassey Lee
3 Fractals and Geography 31
Pierre Frankhauser and Denise Pumain
Project 1 Emergence and Urban Analysis 57
Ljubomir Jankovic
Project 2 The Evolution and Complexity of Urban Street Networks 63
Nahid Mohajeri and Agust Gudmundsson
Section II Machines that Think 69
4 Artificial Intelligence, Logic, and Formalising Common Sense 71
John McCarthy
5 Defining Artificial Intelligence 91
David B. Fogel
6 AI: From Copy of Human Brain to Independent Learner 121
Shelly Fan
7 The History of Machine Learning and Its Convergent Trajectory Towards AI 129
Keith D. Foote
8 Machine Behaviour 143
Iyad 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 Wellman
Project 3 Plan Generation from Program Graph 167
Ao Li, Runjia Tian, Xiaoshi Wang, and Yueheng Lu
Project 4 Self-organising Floor Plans in Care Homes 171
Silvio Carta, Stephanie St. Loe, Tommaso Turchi, and Joel Simon
Project 5 N2P2 - Neural Networks and Public Places 177
Roberto Bottazzi, Tasos Varoudis, Piyush Prajapati, and Xi Wang
Project 6 Urban Fictions 183
Matias del Campo, Sandra Manninger, and Alexandra Carlson
Project 7 Latent Typologies: Architecture in Latent Space 189
Stanislas Chaillou
Project 8 Enabling Alternative Architectures 193
Nate Peters
Project 9 Distant Readings of Architecture: A Machine View of the City 201
Andrew Witt
Section III How Machines Learn 207
9 What Is Machine Learning? 209
Jason Bell
10 Machine Learning: An Applied Mathematics Introduction 217
Paul Wilmott
11 Machine Learning for Urban Computing 249
Bilgeçä Aydo¿du and Albert Ali Salah
12 Autonomous Artificial Intelligent Agents 263
Iaroslav Omelianenko
Project 10 Machine Learning for Spatial and Visual Connectivity 287
Sherif Tarabishy, Stamatios Psarras, Marcin Kosicki, and Martha Tsigkari
Project 11 Navigating Indoor Spaces Using Machine Learning: Train Stations in Paris 293
Zhoutong Wang, Qianhui Liang, Fabio Duarte, Fan Zhang, Louis Charron, Lenna Johnsen, Bill Cai, and Carlo Ratti
Project 12 Evolutionary Design Optimisation of Traffic Signals Applied to Quito City 297
Rolando Armas, Hernán Aguirre, Fabio Daolio, and Kiyoshi Tanaka
Project 13 Constructing Agency: Self-directed Robotic Environments 303
Patrik Schumacher
Section IV Application to the City 309
13 Code and the Transduction of Space 311
Martin Dodge and Rob Kitchin
14 Augmented Reality in Urban Places: Contested Content and the Duplicity of Code 341
Mark Graham, Matthew Zook, and Andrew Boulton
15 Spatial Data in Urban Informatics: Contentions of the Software-sorted City 367
Marcus Foth, Fahame Emamjome, Peta Mitchell, and Markus Rittenbruch
16 Urban Morphology Meets Deep Learning: Exploring Urban Forms in One Million Cities, Towns, and Villages Across the Planet 379
Vahid Moosavi
17 Computational Urban Design: Methods and Case Studies 393
Snoweria Zhang and Luc Wilson
18 Indexical Cities: Personal City Models with Data as Infrastructure 409
Diana Alvarez-Marin
19 Machine Learning, Artificial Intelligence, and Urban Assemblages 445
Serjoscha Düring, Reinhard Koenig, Nariddh Khean, Diellza Elshani, Theodoros Galanos, and Angelos Chronis
20 Making a Smart City Legible 453
Franziska Pilling, Haider Ali Akmal, Joseph Lindley, and Paul Coulton
Project 14 A Tale of Many Cities: Universal Patterns in Human Urban Mobility 467
Anastasios Noulas, Salvatore Scellato, Renaud Lambiotte, Massimiliano Pontil, and Cecilia Mascolo
Project 15 Using Cellular Automata for Parking Recommendations in Smart Environments 473
Gwo-Jiun Horng
Project 16 Gan Hadid 477
Sean Wallish
Project 17 Collective Design for Collective Living 483
Elizabeth Christoforetti and Romy El Sayah
Project 18 Architectural Machine Translation 489
Erik Swahn
Project 19 Large-scale Evaluation of the Urban Street View with Deep Learning Method 495
Hui Wang, Elisabete A. Silva, and Lun Liu
Project 20 Urban Portraits 501
Jose Luis García del Castillo y López
Project 21 ML-City 507
Benjamin Ennemoser
Project 22 Imaging Place Using Generative Adversarial Networks (GAN Loci) 513
Kyle Steinfeld
Project 23 Urban Forestry Science 517
Iacopo Testi
Section V Machine Learning and Humans 521
21 Ten Simple Rules for Responsible Big Data Research 523
Matthew 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 Pasquale
22 A Unified Framework of Five Principles for AI in Society 535
Luciano Floridi and Josh Cowls
23 The Big Data Divide and Its Consequences 547
Matthew T. McCarthy
24 Design Fiction: A Short Essay on Design, Science, Fact, and Fiction 561
Julian Bleecker
25 Superintelligence and Singularity 579
Ray Kurzweil
26 The Social Life of Robots: The Politics of Algorithms, Governance, and Sovereignty 603
Vincent J. Del Casino Jr, Lily House-Peters, Jeremy W. Crampton, and Hannes Gerhardt
Project 24 Experiments in Synthetic Data 615
Forensic Architecture
Project 25 Emotional AI in Cities: Cross-cultural Lessons from the UK and Japan on Designing for an Ethical Life 621
Vian Bakir, Nader Ghotbi, Tung Manh Ho, Alexander Laffer, Peter Mantello, Andrew McStay, Diana Miranda, Hiroshi Miyashita, Lena Podoletz, Hiromi Tanaka, and Lachlan Urquhart
Project 26 Decoding Urban Inequality: The Applications of Machine Learning for Mapping Inequality in Cities of the Global South 625
Kadeem Khan
Project 27 Amsterdam 2040 631
Maria Luce Lupetti
Project 28 Committee of Infrastructure 635
Jason Shun Wong
Index 639
| Erscheinungsjahr: | 2022 |
|---|---|
| Genre: | Kunst |
| Rubrik: | Kunst & Musik |
| Thema: | Architektur |
| Medium: | Taschenbuch |
| Inhalt: | 672 S. |
| ISBN-13: | 9781119749639 |
| ISBN-10: | 1119749638 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Carta, Silvio |
| Redaktion: | Carta, Silvio |
| Herausgeber: | Silvio Carta |
| Hersteller: | Wiley |
| Maße: | 244 x 170 x 36 mm |
| Von/Mit: | Silvio Carta |
| Erscheinungsdatum: | 17.05.2022 |
| Gewicht: | 1,143 kg |
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