This book takes the viewpoint that plain symbol processing techniques have little hope of reproducing the depth and breadth of capabilities found in human beings. The book introduces new foundational principles to AI: connectionist/neural networking methods, case based and memory based methods and picture processing.
The book looks at methods of AI as different ways of doing pattern recognition. One way to do pattern recognition is to compare a problem to stored cases. At the other end of the spectrum, Classical Symbol Processing AI compresses cases down to a small set of rules and then works only with this condensed knowledge. In between these two extremes are neural networks, especially backprop type networks. As much as possible the book compares these three basic methods using actual AI programs.
The structure of the book starts at the bottom of human abilities with vision and other simple pattern recognition abilities and moves on to the higher levels of problem solving and game playing and finally to the level of natural language and understanding of the world. At the higher levels more complex computer architectures are needed that include methods for structuring thoughts.
The book is organized in a manner in which the reader will get an intuitive feeling for the principles of AI. Throughout the book applications of basic principles are demonstrated by examining some classic AI programs in detail. The book can serve as a text for juniors, seniors and first year graduate students in Computer Science or Psychology and includes sample problems and data for exercises and a list of frequently asked questions.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Donald Tveter is the author of The Pattern Recognition Basis of Artificial Intelligence, published by Wiley.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : By The Way Books, Richmond, TX, Etats-Unis
First edition. xiv, 369 pages. Cloth bound in very good condition; A few pages with highlighting. N° de réf. du vendeur 29693
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Vendeur : HPB-Red, Dallas, TX, Etats-Unis
paperback. Etat : Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! N° de réf. du vendeur S_350671931
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Vendeur : Alhambra Books, Edmonton, AB, Canada
Hardcover. Etat : Very Good. 369 pp, index. N° de réf. du vendeur 013093
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Vendeur : Antiquariat Bernhardt, Kassel, Allemagne
gebundene Ausgabe. Etat : Sehr gut. Zust: Gutes Exemplar. Mit Vorbesitzereintrag. XIV, 369 Seiten, Englisch 822g. N° de réf. du vendeur 492633
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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 1162014-n
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Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Paperback. Etat : new. Paperback. This book takes the viewpoint that plain symbol processing techniques have little hope of reproducing the depth and breadth of capabilities found in human beings. The book introduces new foundational principles to AI: connectionist/neural networking methods, case based and memory based methods and picture processing. The book looks at methods of AI as different ways of doing pattern recognition. One way to do pattern recognition is to compare a problem to stored cases. At the other end of the spectrum, Classical Symbol Processing AI compresses cases down to a small set of rules and then works only with this condensed knowledge. In between these two extremes are neural networks, especially backprop type networks. As much as possible the book compares these three basic methods using actual AI programs. The structure of the book starts at the bottom of human abilities with vision and other simple pattern recognition abilities and moves on to the higher levels of problem solving and game playing and finally to the level of natural language and understanding of the world. At the higher levels more complex computer architectures are needed that include methods for structuring thoughts. The book is organized in a manner in which the reader will get an intuitive feeling for the principles of AI. Throughout the book applications of basic principles are demonstrated by examining some classic AI programs in detail. The book can serve as a text for juniors, seniors and first year graduate students in Computer Science or Psychology and includes sample problems and data for exercises and a list of frequently asked questions. This text introduces foundational principles to artificial intelligence (AI), including: connectionist/neural networking methods; case based and memory based methods; and picture processing. It compares these three basic methods using actual AI programmes. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9780818677960
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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 1162014
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Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur FW-9780818677960
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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In. N° de réf. du vendeur ria9780818677960_new
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Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : New. N° de réf. du vendeur 1162014-n
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