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Книги з теми "Computational design history"

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Автор: Grafiati

Опубліковано: 10 грудня 2022

Оновлено: 28 січня 2023

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1

1961-, Fuss Adam, Linn Judy, and Matthew Marks Gallery, eds. Terry Winters: Computation of chains. New York, N.Y: Matthew Marks Gallery, 1997.

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2

ZnO bao mo zhi bei ji qi guang, dian xing neng yan jiu. Shanghai Shi: Shanghai da xue chu ban she, 2010.

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3

Digital Architecture Beyond Computers: Fragments of a Cultural History of Computational Design. Bloomsbury Publishing Plc, 2021.

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4

Bottazzi, Roberto. Digital Architecture Beyond Computers: Fragments of a Cultural History of Computational Design. Bloomsbury Publishing Plc, 2018.

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5

O'Regan, Gerard. Guide to Discrete Mathematics: An Accessible Introduction to the History, Theory, Logic and Applications. Springer International Publishing AG, 2022.

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6

O'Regan, Gerard. Guide to Discrete Mathematics: An Accessible Introduction to the History, Theory, Logic and Applications. Springer International Publishing AG, 2016.

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7

Guide to Discrete Mathematics: An Accessible Introduction to the History, Theory, Logic and Applications. Springer, 2016.

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8

O'Regan, Gerard. Guide to Discrete Mathematics: An Accessible Introduction to the History, Theory, Logic and Applications. Springer International Publishing AG, 2021.

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9

O'Regan, Gerard. Guide to Discrete Mathematics: An Accessible Introduction to the History, Theory, Logic and Applications. Springer, 2018.

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10

Chen, Shu-Heng, Mak Kaboudan, and Ye-Rong Du, eds. The Oxford Handbook of Computational Economics and Finance. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199844371.001.0001.

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Анотація:

Being published as a celebration of the 60th anniversary of John von Neumann’s “Theory of Self-Reproducing Automata,” this handbook attempts to provide a unique reflection on the nature of computational economics and finance (CEF) in light of natural computationalism. We restructure CEF by including both nature-inspired computing and natural computing. This new framework allows us to have a view of CEF much broader than just the conventional algorithmic consideration. The book begins with a historical review of computational economics (CE), tracing its history far back to the era of analog computing. In these early days, advancements were mainly made using the idea of natural computing, and the subjects pursued by CE were the computing system as a whole, not just numerical computing. The handbook then is organized by distinguishing computing from computing systems. Six chapters (Chapters 2 to 7) are devoted to the former. They together present a review on the recent progresses in CE, as illustrated by the computation of rational expectations, general equilibrium, risk, and volatility. The subsequent 16 chapters are devoted to the computing-systemic view of CE, including natural-inspired computing (Chapters 8 to 12) and network, agent-based computing and neural computing (Chapters 13 to 23). In addition to providing alternative approaches to forecasting, investment strategies and risk management, etc., they enable us to have a 'natural' or more realistic description of the economy, starting from its decision makers; hence, market-design or policy-design issues involving different levels of the economy, be microscopic, mesoscopic and macroscopic, can be simultaneously addressed and coherently integrated. The handbook concludes with a chapter on what we may hope from CE by providing an in-depth review on the epistemological aspects of computation.

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11

Dean, Roger T., and Alex McLean, eds. The Oxford Handbook of Algorithmic Music. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190226992.001.0001.

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Algorithmic music appears to be at a turning point in its history, with many new systems and communities of practice developing together, as vibrant musical culture. This handbook brings together dozens of leading researchers and practitioners in the field, blending technical, artistic, cultural and scientific viewpoints into a whole that considers the making of algorithmic music as a rich, and essentially human activity. The book is organised into four sections, the first grounding the topic in the history, philosophy and psychology of algorithmic music. The second section asks 'what can algorithms in music do?', finding answers in computer science, mathematics, machine learning, bio-inspired computation, manipulation of pattern, computational creativity, and live coding. The third section focuses on the music maker, and the role of algorithms in supporting network music, sonification, music interface design, music in computer games, and spatialisation. The final section opens out to culture at large, and considers algorithmic music in terms of its audience reception, sociology, education, politics and the potential for mass consumption. Perhaps just as importantly, these sections are interleaved with reflective pieces from leading practitioners in the field, allowing us to to grasp the pragmatics of making music with algorithms. Combined, these diverse standpoints provide an absorbing, authoritative survey of research and practice from across the algorithmic music field.

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12

Dasgupta, Subrata. The Second Age of Computer Science. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190843861.001.0001.

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Анотація:

By the end of the 1960s, a new discipline named computer science had come into being. A new scientific paradigm--the 'computational paradigm'--was in place, suggesting that computer science had reached a certain level of maturity. Yet as a science it was still precociously young. New forces, some technological, some socio-economic, some cognitive impinged upon it, the outcome of which was that new kinds of computational problems arose over the next two decades. Indeed, by the beginning of the 1990's the structure of the computational paradigm looked markedly different in many important respects from how it was at the end of the 1960s. Author Subrata Dasgupta named the two decades from 1970 to 1990 as the second age of computer science to distinguish it from the preceding genesis of the science and the age of the Internet/World Wide Web that followed. This book describes the evolution of computer science in this second age in the form of seven overlapping, intermingling, parallel histories that unfold concurrently in the course of the two decades. Certain themes characteristic of this second age thread through this narrative: the desire for a genuine science of computing; the realization that computing is as much a human experience as it is a technological one; the search for a unified theory of intelligence spanning machines and mind; the desire to liberate the computational mind from the shackles of sequentiality; and, most ambitiously, a quest to subvert the very core of the computational paradigm itself. We see how the computer scientists of the second age address these desires and challenges, in what manner they succeed or fail and how, along the way, the shape of computational paradigm was altered. And to complete this history, the author asks and seeks to answer the question of how computer science shows evidence of progress over the course of its second age.

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13

Computational Mechanics For Heritage Structures (High Performance Structures and Materials). WIT Press (UK), 2006.

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14

Nerbonne, John. Natural Language Processing in Computer-Assisted Language Learning. Edited by Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0037.

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This article examines the application of natural language processing to computer-assisted language learning (CALL) including the history of work in this field over the last thirtyfive years and focuses on current developments and opportunities. It always refers to programs designed to help people learn foreign languages. CALL is a large field — much larger than computational linguistics. This article outlines the areas of CALL to which computational linguistics (CL) can be applied. CL programs process natural languages such as English and Spanish, and the techniques are therefore often referred to as natural language processing (NLP). NLP is enlisted in several ways in CALL to provide lemmatized access to corpora for advanced learners seeking subtleties unavailable in grammars and dictionaries. It also provides morphological analysis and subsequent dictionary access for words unknown to readers and to parse user input and diagnose morphological and syntactic errors.

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15

Anderson, James A. After Digital. Oxford University Press, 2018. http://dx.doi.org/10.1093/acprof:oso/9780199357789.001.0001.

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Анотація:

We are surrounded by digital computers. They do many things well that humans do not and have transformed our lives. But all computers are not the same. Although digital computers dominate today’s world, alternative ways to “compute” might be better and more efficient than digital computation when mechanically performing those tasks, important to humans, that we think of as “cognition.” Cognition, after all, was originally developed to work with our own specific biological hardware. Digital computers require elaborate detailed instructions to work; they are flexible but not simple. Analog computers are designed to do specific tasks. They can be simple but not flexible. Hardware matters. The book discusses two classic kinds of computer, digital and analog, and gives examples of their history, functions, and limitations. The author suggest that when brain “hardware,” with its associated brain “software” work together, it could form a computer architecture that would be useful for the efficient performance of cognitive tasks. This book discusses the essentials of brain hardware—in particular, the cerebral cortex, where cognition lives—and how cortical structure can influence the form taken by the computational operations underlying cognition. Topics include association, understanding complex systems through analogy, formation of abstractions, and the biology of number and its use in arithmetic and mathematics. The author introduces novel “brain-like” control mechanisms: active associative search and traveling waves. There is discussion on computing across scales of organization from single neurons to brain regions containing millions of neurons.

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16

Winters, Terry, and Adam Fuss. Terry Winters: Computation of Chains. Matthew Marks Gallery, 1997.

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17

Sandvig, Christian. The Internet as Infrastructure. Edited by William H. Dutton. Oxford University Press, 2013. http://dx.doi.org/10.1093/oxfordhb/9780199589074.013.0005.

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Анотація:

This chapter discusses how useful it can be to view the Internet as an infrastructure, demonstrating how technical changes of the infrastructure can have unanticipated and unintended societal consequences. The Libyan decision induced substantial dismay in the Internet industry. The case of Violet Blue entails technical decisions about the design of interactive software, usability, culture, religion, history, politics, and economics. Moreover, the infrastructure studies of the Internet are outlined as the relationists and the new materialists. The Internet turns out as an infrastructural primitive or template for its parents: a model privately organized system of distributed computation – theur-infrastructure. Communication in its original meaning was transportation, a box of goods was said to be ‘communicated’ when it was delivered. It is observed that the Internet demands attention as a foundation for modern life.

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