Machine learning, artificial intelligence and urban assemblages :  applications in architecture and urban design / 
edited by Silvio Carta. 
 - xxx, 642 pages :  illustrations ;  24 cm. 
<br/><br/>Includes bibliographical references and index. 
<br/><br/>Section I. Urban complexity -- Urban complexity -- Emergence and universal computation -- Fractals and geography -- Section II. machines that thinks -- Artificial intelligence, logic, and formalising common sense -- Defining artificial intelligence -- AI: from copy of human brain to independent learner -- The history of machine learning and its convergent trajectory towards AI -- Machine behavior -- Section III. How machines learn -- What is machine learning? -- machine learning: an applied mathematics introduction -- Machine learning for urban computing -- Autonomous artificial intelligent agents -- Section IV. Application to the city -- Code and the transduction of space -- Augmented reality in urban places: contested content and the duplicity of code -- Spatial data in urban informatics: contentions of the software-sorted city -- Urban morphology meets deep learning: exploring urban forms in one million cities, towns, and villages across the planet -- Computational urban design: methods and case studies -- Indexical cities: personal city models with data as infrastructure -- Machine learning, artificial intelligence, and urban assemblages -- Making a smart city legible -- Using cellular automata for parking recommendations in smart environments -- Section V. Machine learning and humans -- Ten simple rules for responsible big data research -- A unified framework of five principles for AI in society -- The big data divide and its consequences -- Design fiction: a short essay on design, science, fact, and fiction -- Superintelligence and singularity -- The social life of robots: the politics of algorithms, governance, and sovereignty.  
<br/><br/> "The twentieth century is replete with scientific and mathematical discoveries that have profoundly changed our world view. In physics, within a mere century, our view of the cosmos changed from a classical (Newtonian) to a relativistic one following Einstein's relativity theory in the early 1900s. In mathematics, Hilbert's faith in the closure of formal axiom systems fell apart with Gödel's incompleteness theorem in the 1930s. Out of these ashes of lost deterministic foundations arose the sciences of complex systems, first in the study of non-equilibrium thermodynamics (under the intellectual leadership of Ilya Prigogine in Brussels) and later, in broader interdisciplinary terms, in New Mexico with the establishment of the Santa Fe Institute. Interestingly, a core element of this new paradigm-the notion of emergence-reflects the passage of the sciences and mathematics from a focus on closed and deterministic systems to open and dissipative systems where order, structure or patterns arise seemingly out of nowhere (at least as far as initial and boundary conditions are concerned)."-- 
<br/><br/><label>ISBN: </label>9781119749639 
<br/><br/><label>LCCN: </label>2021052711 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Architecture and technology.<br/>City planning.<br/>Machine learning.<br/>Artificial intelligence.
<br/><br/><label>LC Class. No.: </label>NA2543.T43  / C375 2022 
<br/><br/><label>Dewey Class. No.: </label>711.40285  / M184