Thinking As Computation
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| Author | : Hector J. Levesque |
| Publisher | : MIT Press |
| Total Pages | : 323 |
| Release | : 2012-01-06 |
| Genre | : Computers |
| ISBN | : 0262300648 |
Students explore the idea that thinking is a form of computation by learning to write simple computer programs for tasks that require thought. This book guides students through an exploration of the idea that thinking might be understood as a form of computation. Students make the connection between thinking and computing by learning to write computer programs for a variety of tasks that require thought, including solving puzzles, understanding natural language, recognizing objects in visual scenes, planning courses of action, and playing strategic games. The material is presented with minimal technicalities and is accessible to undergraduate students with no specialized knowledge or technical background beyond high school mathematics. Students use Prolog (without having to learn algorithms: “Prolog without tears!”), learning to express what they need as a Prolog program and letting Prolog search for answers. After an introduction to the basic concepts, Thinking as Computation offers three chapters on Prolog, covering back-chaining, programs and queries, and how to write the sorts of Prolog programs used in the book. The book follows this with case studies of tasks that appear to require thought, then looks beyond Prolog to consider learning, explaining, and propositional reasoning. Most of the chapters conclude with short bibliographic notes and exercises. The book is based on a popular course at the University of Toronto and can be used in a variety of classroom contexts, by students ranging from first-year liberal arts undergraduates to more technically advanced computer science students.
| Author | : Peter J. Denning |
| Publisher | : MIT Press |
| Total Pages | : 266 |
| Release | : 2019-05-14 |
| Genre | : Computers |
| ISBN | : 0262353423 |
This pocket-sized introduction to computational thinking and problem-solving traces its genealogy centuries before the digital computer. A few decades into the digital era, scientists discovered that thinking in terms of computation made possible an entirely new way of organizing scientific investigation. Eventually, every field had a computational branch: computational physics, computational biology, computational sociology. More recently, “computational thinking” has become part of the K–12 curriculum. But what is computational thinking? This volume in the MIT Press Essential Knowledge series offers an accessible overview—tracing a genealogy that begins centuries before digital computers and portraying computational thinking as the pioneers of computing have described it. The authors explain that computational thinking (CT) is not a set of concepts for programming; it is a way of thinking that is honed through practice: the mental skills for designing computations to do jobs for us, and for explaining and interpreting the world as a complex of information processes. Mathematically trained experts (known as “computers”) who performed complex calculations as teams engaged in CT long before electronic computers. In each chapter, the author identify different dimensions of today's highly developed CT: • Computational Methods • Computing Machines • Computing Education • Software Engineering • Computational Science • Design Along the way, they debunk inflated claims for CT and computation while making clear the power of CT in all its complexity and multiplicity.
| Author | : Achim Menges |
| Publisher | : John Wiley & Sons |
| Total Pages | : 230 |
| Release | : 2011-10-24 |
| Genre | : Architecture |
| ISBN | : 047066570X |
The current transition from Computer Aided Design (CAD) to Computational Design in architecture represents a profound shift in design thinking and methods. Representation is being replaced by simulation, and the crafting of objects is moving towards the generation of integrated systems through designer-authored computational processes. While there is a particular history of such an approach in architecture, its relative newness requires the continued progression of novel modes of design thinking for the architect of the 21st century. This AD Reader establishes a foundation for such thinking. It includes multifaceted reflections and speculations on the profound influence of computational paradigms on architecture. It presents relevant principles from the domains of mathematics and computer science, developmental and evolutionary biology, system science and philosophy, establishing a discourse for computational design thinking in architecture. Rather than a merely technical approach, the book will discuss essential intellectual concepts that are fundamental not only for a discourse on computational design but also for its practice. This anthology provides a unique collection of seminal texts by authors, who have either provided a significant starting point through which a computational approach to design has been pursued or have played a considerable role in shaping the field. An important aspect of this book is the manner in which adjacent fields and historical texts are connected. Both the source of original inspiration and scientific thought are presented alongside contemporary writings on the continually evolving computational design discourse. Emerging from the field of science, principally the subjects of morphogenesis, evolution and mathematics, selected texts provide a historical basis for a reconfigured mindset of processes that generate, arrange and describe form. Juxtaposed against more contemporary statements regarding the influence of computation on design thinking, the book offers advancements of fundamental texts to the particular purpose of establishing novel thought processes for architecture, theoretically and practically. The first reader to provide an effective framework for computational thinking in design. Includes classic texts by Johan W. von Goethe, D’Arcy Thompson, Ernst Mayr, Ludwig von Bertalanffy, Gordan Pask, Christopher Alexander, John H. Holland, Nicholas Negroponte, William Mitchell, Peter J. Bentley & David W. Corne, Sanford Kwinter, John Frazer, Kostis Terzidis, Michael Weinstock and Achim Menges Features new writing by: Mark Burry, Jane Burry, Manuel DeLanda and Peter Trummer.
| Author | : John Maeda |
| Publisher | : Penguin |
| Total Pages | : 242 |
| Release | : 2019-11-12 |
| Genre | : Technology & Engineering |
| ISBN | : 0399564438 |
Visionary designer and technologist John Maeda defines the fundamental laws of how computers think, and why you should care even if you aren't a programmer. "Maeda is to design what Warren Buffett is to finance." --Wired John Maeda is one of the world's preeminent interdisciplinary thinkers on technology and design. In How to Speak Machine, he offers a set of simple laws that govern not only the computers of today, but the unimaginable machines of the future. Technology is already more powerful than we can comprehend, and getting more powerful at an exponential pace. Once set in motion, algorithms never tire. And when a program's size, speed, and tirelessness combine with its ability to learn and transform itself, the outcome can be unpredictable and dangerous. Take the seemingly instant transformation of Microsoft's chatbot Tay into a hate-spewing racist, or how crime-predicting algorithms reinforce racial bias. How to Speak Machine provides a coherent framework for today's product designers, business leaders, and policymakers to grasp this brave new world. Drawing on his wide-ranging experience from engineering to computer science to design, Maeda shows how businesses and individuals can identify opportunities afforded by technology to make world-changing and inclusive products--while avoiding the pitfalls inherent to the medium.
| Author | : Maureen D. Neumann |
| Publisher | : MIT Press |
| Total Pages | : 201 |
| Release | : 2021-12-21 |
| Genre | : Computers |
| ISBN | : 0262045052 |
A guide for educators to incorporate computational thinking—a set of cognitive skills applied to problem solving—into a broad range of subjects. Computational thinking—a set of mental and cognitive tools applied to problem solving—is a fundamental skill that all of us (and not just computer scientists) draw on. Educators have found that computational thinking enhances learning across a range of subjects and reinforces students’ abilities in reading, writing, and arithmetic. This book offers a guide for incorporating computational thinking into middle school and high school classrooms, presenting a series of activities, projects, and tasks that employ a range of pedagogical practices and cross a variety of content areas. As students problem solve, communicate, persevere, work as a team, and learn from mistakes, they develop a concrete understanding of the abstract principles used in computer science to create code and other digital artifacts. The book guides students and teachers to integrate computer programming with visual art and geometry, generating abstract expressionist–style images; construct topological graphs that represent the relationships between characters in such literary works as Harry Potter and the Sorcerer’s Stone and Romeo and Juliet; apply Newtonian physics to the creation of computer games; and locate, analyze, and present empirical data relevant to social and political issues. Finally, the book lists a variety of classroom resources, including the programming languages Scratch (free to all) and Codesters (free to teachers). An accompanying website contains the executable programs used in the book’s activities.
| Author | : Siu-Cheung Kong |
| Publisher | : Springer |
| Total Pages | : 377 |
| Release | : 2019-07-04 |
| Genre | : Education |
| ISBN | : 9811365288 |
This This book is open access under a CC BY 4.0 license.This book offers a comprehensive guide, covering every important aspect of computational thinking education. It provides an in-depth discussion of computational thinking, including the notion of perceiving computational thinking practices as ways of mapping models from the abstraction of data and process structures to natural phenomena. Further, it explores how computational thinking education is implemented in different regions, and how computational thinking is being integrated into subject learning in K-12 education. In closing, it discusses computational thinking from the perspective of STEM education, the use of video games to teach computational thinking, and how computational thinking is helping to transform the quality of the workforce in the textile and apparel industry.
| Author | : John V. Guttag |
| Publisher | : MIT Press |
| Total Pages | : 466 |
| Release | : 2016-08-12 |
| Genre | : Computers |
| ISBN | : 0262529629 |
The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.
| Author | : Paolo Ferragina |
| Publisher | : Springer |
| Total Pages | : 176 |
| Release | : 2018-08-21 |
| Genre | : Computers |
| ISBN | : 331997940X |
This book offers a gentle motivation and introduction to computational thinking, in particular to algorithms and how they can be coded to solve significant, topical problems from domains such as finance, cryptography, Web search, and data compression. The book is suitable for undergraduate students in computer science, engineering, and applied mathematics, university students in other fields, high-school students with an interest in STEM subjects, and professionals who want an insight into algorithmic solutions and the related mindset. While the authors assume only basic mathematical knowledge, they uphold the scientific rigor that is indispensable for transforming general ideas into executable algorithms. A supporting website contains examples and Python code for implementing the algorithms in the book.
| Author | : Robert Kowalski |
| Publisher | : |
| Total Pages | : 310 |
| Release | : 2011 |
| Genre | : Communication |
| ISBN | : 9781107214453 |
"The practical benefits of computational logic need not be limited to mathematics and computing. As this book shows, ordinary people in their everyday lives can profit from the recent advances that have been developed for artificial intelligence. The book draws upon related developments in various fields from philosophy to psychology and law. It pays special attention to the integration of logic with decision theory, and the use of logic to improve the clarity and coherence of communication in natural languages such as English. This book is essential reading for teachers and researchers who may be out of touch with the latest developments in computational logic. It will also be useful in any undergraduate course that teaches practical thinking, problem solving or communication skills. Its informal presentation makes the book accessible to readers from any background, but optional, more formal, chapters are also included for those who are more technically oriented"--
| Author | : Zenon W. Pylyshyn |
| Publisher | : National Geographic Books |
| Total Pages | : 0 |
| Release | : 1986-02-07 |
| Genre | : Psychology |
| ISBN | : 026266058X |
The question, "What is Cognitive Science?" is often asked but seldom answered to anyone's satisfaction. Until now, most of the answers have come from the new breed of philosophers of mind. This book, however, is written by a distinguished psychologist and computer scientist who is well-known for his work on the conceptual foundations of cognitive science, and especially for his research on mental imagery, representation, and perception. In Computation and Cognition, Pylyshyn argues that computation must not be viewed as just a convenient metaphor for mental activity, but as a literal empirical hypothesis. Such a view must face a number of serious challenges. For example, it must address the question of "strong equivalents" of processes, and must empirically distinguish between phenomena which reveal what knowledge the organism has, phenomena which reveal properties of the biologically determined "functional architecture" of the mind. The principles and ideas Pylyshyn develops are applied to a number of contentious areas of cognitive science, including theories of vision and mental imagery. In illuminating such timely theoretical problems, he draws on insights from psychology, theoretical computer science, artificial intelligence, and psychology of mind. A Bradford Book
