Computers and Thought: a Practical Introduction to Artificial Intelligence PDF Download
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Author:
Publisher:
ISBN: 9780262192859
Category : Anlayış Yeteneği
Languages : en
Pages :
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Book Description
Author:
Publisher:
ISBN: 9780262192859
Category : Anlayış Yeteneği
Languages : en
Pages :
Get Book Here
Book Description
Author:
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 0
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Book Description
Author: Edward A Feigenbaum
Publisher:
ISBN: 9781258241780
Category :
Languages : en
Pages : 548
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Book Description
Computers and Thought showcases the work of the scientists who not only defined the field of Artificial Intelligence, but who are responsible for having developed it into what it is today. Originally published in 1963, this collection includes twenty classic papers by such pioneers as A. M. Turing and Marvin Minsky who were behind the pivotal advances in artificially simulating human thought processes with computers.
Author: Mike Sharples
Publisher: Springer Science & Business
ISBN: 9780262691338
Category : Computers
Languages : en
Pages : 444
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Book Description
Computers and Thought provides a unified, self-contained introduction to artificial intelligence for readers with little or no computing background. It presents an original extended AI programming project - the Automated Tourist Guide exercise throughout the main chapters of the text to illustrate the material covered and show how AI actually works. Most chapters illustrate a particular AI topic, with sections on the background to the topic, methods, applications, and the limitations of previous proposals. In addition, there are end of chapter summaries and graded exercises, suggested readings, a glossary, and an appendix on programming. Computers and Thought details the theory and issues involved in AI and covers computer simulation of human activities, such as problem solving and natural language understanding, and computer vision. Its investigation of AI is usefully extended to models of cognition, the nature of mind and intelligence, and the social implications of AI and cognitive science. The computer language is POP-11, an easy to learn language that can be used interactively, like LISP, and that has an appearance similar to PASCAL. It is not necessary to run the illustrative POP-11 programs on a computer, since a feature of the language is the ease with which it can be understood from the printed page. Computers and Thought is included in the series Explorations in Cognitive Science, edited by Margaret A Boden. A Bradford Book
Author: Matt Carter
Publisher: Edinburgh University Press
ISBN: 0748629300
Category : Philosophy
Languages : en
Pages : 240
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Book Description
Could a computer have a mind? What kind of machine would this be? Exactly what do we mean by 'mind' anyway?The notion of the 'intelligent' machine, whilst continuing to feature in numerous entertaining and frightening fictions, has also been the focus of a serious and dedicated research tradition. Reflecting on these fictions, and on the research tradition that pursues 'Artificial Intelligence', raises a number of vexing philosophical issues. Minds and Computers introduces readers to these issues by offering an engaging, coherent, and highly approachable interdisciplinary introduction to the Philosophy of Artificial Intelligence.Readers are presented with introductory material from each of the disciplines which constitute Cognitive Science: Philosophy, Neuroscience, Psychology, Computer Science, and Linguistics. Throughout, readers are encouraged to consider the implications of this disparate and wide-ranging material for the possibility of developing machines with minds. And they can expect to de
Author: Wolfgang Ertel
Publisher: Springer
ISBN: 3319584871
Category : Computers
Languages : en
Pages : 365
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Book Description
This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning. Fully revised and updated, this much-anticipated second edition also includes new material on deep learning. Topics and features: presents an application-focused and hands-on approach to learning, with supplementary teaching resources provided at an associated website; contains numerous study exercises and solutions, highlighted examples, definitions, theorems, and illustrative cartoons; includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning; reports on developments in deep learning, including applications of neural networks to generate creative content such as text, music and art (NEW); examines performance evaluation of clustering algorithms, and presents two practical examples explaining Bayes’ theorem and its relevance in everyday life (NEW); discusses search algorithms, analyzing the cycle check, explaining route planning for car navigation systems, and introducing Monte Carlo Tree Search (NEW); includes a section in the introduction on AI and society, discussing the implications of AI on topics such as employment and transportation (NEW). Ideal for foundation courses or modules on AI, this easy-to-read textbook offers an excellent overview of the field for students of computer science and other technical disciplines, requiring no more than a high-school level of knowledge of mathematics to understand the material.
Author: Richard Bellman
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 146
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Book Description
Author: Edward A. Feigenbaum
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 574
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Book Description
Computers and Thought showcases the work of the scientists who not only defined the field of Artificial Intelligence, but who are responsible for having developed it into what it is today. Originally published in 1963, this collection includes twenty classic papers by such pioneers as A. M. Turing and Marvin Minsky who were behind the pivotal advances in artificially simulating human thought processes with computers. Among the now hard-to-find articles are reports of computer programs that play chess and checkers, prove theorems in logic and geometry, solve problems in calculus, balance assembly lines, recognize visual temporal patterns, and communicate in natural language. The reports of simulation of cognitive processes include computer models of human behavior in logic problems, deciding on common stock portfolios, and carrying out social interaction. Models of verbal learning behavior, predictive behavior in two-choice experiments, and concept formation are also included. Articles by : Paul Armer. Carol Chomsky. Geoffrey P. E. Clarkson. Edward A. Feigenbaum. Julian Feldman. H. Gelernter. Bert F. Green, Jr. John T. Gullahorn. Jeanne E. Gullahorn. J. R. Hansen. Carl I. Hovland. Earl B. Hunt. Kenneth Laughery. Robert K. Lindsay. D. W. Loveland. Marvin Minsky. Ulric Neisser. Allen Newell. A. L. Samuel. Oliver G. Selfridge. J. C. Shaw. Herbert A. Simon. James R. Slagle. Fred M. Tonge. A. M. Turing. Leonard Uhr. Charles Vossler. Alice K. Wolf.
Author: Philip C. Jackson
Publisher: Courier Dover Publications
ISBN: 0486832864
Category : Computers
Languages : en
Pages : 545
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Book Description
Can computers think? Can they use reason to develop their own concepts, solve complex problems, understand our languages? This updated edition of a comprehensive survey includes extensive new text on "Artificial Intelligence in the 21st Century," introducing deep neural networks, conceptual graphs, languages of thought, mental models, metacognition, economic prospects, and research toward human-level AI. Ideal for both lay readers and students of computer science, the original text features abundant illustrations, diagrams, and photographs as well as challenging exercises. Lucid, easy-to-read discussions examine problem-solving methods and representations, game playing, automated understanding of natural languages, heuristic search theory, robot systems, heuristic scene analysis, predicate-calculus theorem proving, automatic programming, and many other topics.
Author: Erik J. Larson
Publisher: Harvard University Press
ISBN: 0674983513
Category : Computers
Languages : en
Pages : 321
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Book Description
“Artificial intelligence has always inspired outlandish visions—that AI is going to destroy us, save us, or at the very least radically transform us. Erik Larson exposes the vast gap between the actual science underlying AI and the dramatic claims being made for it. This is a timely, important, and even essential book.” —John Horgan, author of The End of Science Many futurists insist that AI will soon achieve human levels of intelligence. From there, it will quickly eclipse the most gifted human mind. The Myth of Artificial Intelligence argues that such claims are just that: myths. We are not on the path to developing truly intelligent machines. We don’t even know where that path might be. Erik Larson charts a journey through the landscape of AI, from Alan Turing’s early work to today’s dominant models of machine learning. Since the beginning, AI researchers and enthusiasts have equated the reasoning approaches of AI with those of human intelligence. But this is a profound mistake. Even cutting-edge AI looks nothing like human intelligence. Modern AI is based on inductive reasoning: computers make statistical correlations to determine which answer is likely to be right, allowing software to, say, detect a particular face in an image. But human reasoning is entirely different. Humans do not correlate data sets; we make conjectures sensitive to context—the best guess, given our observations and what we already know about the world. We haven’t a clue how to program this kind of reasoning, known as abduction. Yet it is the heart of common sense. Larson argues that all this AI hype is bad science and bad for science. A culture of invention thrives on exploring unknowns, not overselling existing methods. Inductive AI will continue to improve at narrow tasks, but if we are to make real progress, we must abandon futuristic talk and learn to better appreciate the only true intelligence we know—our own.
