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Language Machines questions any easily progressive model of technological change, demonstrating the persistence rather than the obsolescence of language technologies over time, the continuous and complicated overlap of pens, presses, screens and voice. In these essays new technologies do not simply replace, but rather draw upon, absorb, displace and resituate earlier technologies.
A Concise Introduction to Languages, Machines and Logic provides an accessible introduction to three key topics within computer science: formal languages, abstract machines and formal logic. Written in an easy-to-read, informal style, this textbook assumes only a basic knowledge of programming on the part of the reader. The approach is deliberately non-mathematical, and features: - Clear explanations of formal notation and jargon, - Extensive use of examples to illustrate algorithms and proofs, - Pictorial representations of key concepts, - Chapter opening overviews providing an introduction and guidance to each topic, - End-of-chapter exercises and solutions, - Offers an intuitive approach to the topics. This reader-friendly textbook has been written with undergraduates in mind and will be suitable for use on course covering formal languages, formal logic, computability and automata theory. It will also make an excellent supplementary text for courses on algorithm complexity and compilers.
"The phonograph and the typewriter may be things of the past, but this book will resonate with readers who are engaged daily with computer networks, hypertexts, and the forms that mass media will take in the new century."--BOOK JACKET.
An up-to-date, authoritative text for courses in theory of computability and languages. The authors redefine the building blocks of automata theory by offering a single unified model encompassing all traditional types of computing machines and real world electronic computers. This reformulation of computablity and formal language theory provides a framework for building a body of knowledge. A solutions manual and an instructor's software disk are also available.
A well-written and accessible introduction to the most important features of formal languages and automata theory. It focuses on the key concepts, illustrating potentially intimidating material through diagrams and pictorial representations, and this edition includes new and expanded coverage of topics such as: reduction and simplification of material on Turing machines; complexity and O notation; propositional logic and first order predicate logic. Aimed primarily at computer scientists rather than mathematicians, algorithms and proofs are presented informally through examples, and there are numerous exercises (many with solutions) and an extensive glossary.
Mentality and Machines was first published in 1985. Minnesota Archive Editions uses digital technology to make long-unavailable books once again accessible, and are published unaltered from the original University of Minnesota Press editions. Mentality and Machines — with a new preface and an extended postscript—is a general essay on the philosophy of mind, oriented to philosophical and psychological questions about real as well as imagined, robots and machines. The second edition retains all of the essays from the original book, including Gunderson's influential critique ("The Imitation Game") of A.M. Turing's treatment of the question "Can machines think?" and his controversial distinction between program-receptive and program-resistant aspects of the mind. This edition's postscript includes further reflections on these themes and others, and relates them to recent writings of other philosophers and computer scientists.
This book shares Chinese scholars’ philosophical views on artificial intelligence. The discussions range from the foundations of AI—the Turing test and creation of machine intelligence—to recent applications of AI, including decisions in games, natural languages, pattern recognition, prediction in economic contexts, autonomous behaviors, and collaborative intelligence, with the examples of AlphaGo, Microsoft’s Xiao Bing, medical robots, etc. The book’s closing chapter focuses on Chinese machines and explores questions on the cultural background of artificial intelligence. Given its scope, the book offers a valuable resource for all members of the general public who are interested in the future development of artificial intelligence, especially from the perspective of respected Chinese scholars.
A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques. This textbook provides a technical perspective on natural language processing—methods for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation. The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.