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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…mehr
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.
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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).
Inhaltsangabe
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 Bilgeça Aydodu and Albert Ali Salah
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
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 Bilgeça Aydodu and Albert Ali Salah
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
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