Introduction to Artificial Intelligence (Undergraduate Topics in Computer Science)

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9780857292988: Introduction to Artificial Intelligence (Undergraduate Topics in Computer Science)

This concise and accessible textbook supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. The book presents concrete algorithms and applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks and reinforcement learning. Topics and features: presents an application-focused and hands-on approach to learning the subject; provides study exercises of varying degrees of difficulty at the end of each chapter, with solutions given at the end of the book; supports the text with highlighted examples, definitions, and theorems; includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning; contains an extensive bibliography for deeper reading on further topics; supplies additional teaching resources, including lecture slides and training data for learning algorithms, at an associated website.

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From the Back Cover:

The ultimate aim of artificial intelligence (A.I.) is to understand intelligence and to build intelligent software and robots that come close to the performance of humans. On their way towards this goal, A.I. researchers have developed a number of quite different subdisciplines.

This concise and accessible Introduction to Artificial Intelligence supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. The textbook presents concrete algorithms and applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks and reinforcement learning.

Topics and features:

  • Presents an application-focused and hands-on approach to learning the subject
  • Provides study exercises of varying degrees of difficulty at the end of each chapter, with solutions given at the end of the book
  • Supports the text with 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
  • Contains an extensive bibliography for deeper reading on further topics
  • Supplies additional teaching resources, including lecture slides and training data for learning algorithms, at the website http://www.hs-weingarten.de/~ertel/aibook

Students of computer science and other technical natural sciences will find this easy-to-read textbook excellent for self-study, a high-school level of knowledge of mathematics being the only prerequisite to understanding the material. With its extensive tools and bibliography, it is an ideal, quick resource on A.I.

Dr. Wolfgang Ertel is a professor at the Collaborative Center for Applied Research on Service Robotics at the Ravensburg-Weingarten University of Applied Sciences, Germany.

About the Author:

Dr. Wolfgang Ertel is a professor at the Collaborative Center for Applied Research on Service Robotics at the Ravensburg-Weingarten University of Applied Sciences, Germany.

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Wolfgang Ertel
Editore: Springer London Ltd, United Kingdom (2011)
ISBN 10: 0857292986 ISBN 13: 9780857292988
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Descrizione libro Springer London Ltd, United Kingdom, 2011. Paperback. Condizione libro: New. 2011. Language: English . Brand New Book. This concise and accessible textbook supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. The book presents concrete algorithms and applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks and reinforcement learning. Topics and features: presents an application-focused and hands-on approach to learning the subject; provides study exercises of varying degrees of difficulty at the end of each chapter, with solutions given at the end of the book; supports the text with highlighted examples, definitions, and theorems; includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning; contains an extensive bibliography for deeper reading on further topics; supplies additional teaching resources, including lecture slides and training data for learning algorithms, at an associated website. Codice libro della libreria AAZ9780857292988

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Wolfgang Ertel, Florian Mast, Nathanael T. Black
Editore: Springer 2011-03-15 (2011)
ISBN 10: 0857292986 ISBN 13: 9780857292988
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Descrizione libro Springer 2011-03-15, 2011. Paperback. Condizione libro: New. Codice libro della libreria NU-GRD-05253140

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Wolfgang Ertel
Editore: Springer London Ltd, United Kingdom (2011)
ISBN 10: 0857292986 ISBN 13: 9780857292988
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Descrizione libro Springer London Ltd, United Kingdom, 2011. Paperback. Condizione libro: New. 2011. Language: English . Brand New Book. This concise and accessible textbook supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. The book presents concrete algorithms and applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks and reinforcement learning. Topics and features: presents an application-focused and hands-on approach to learning the subject; provides study exercises of varying degrees of difficulty at the end of each chapter, with solutions given at the end of the book; supports the text with highlighted examples, definitions, and theorems; includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning; contains an extensive bibliography for deeper reading on further topics; supplies additional teaching resources, including lecture slides and training data for learning algorithms, at an associated website. Codice libro della libreria AAZ9780857292988

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Wolfgang Ertel (author), Nathanael T. Black (translator)
Editore: Springer London 2011-03-15, London (2011)
ISBN 10: 0857292986 ISBN 13: 9780857292988
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Descrizione libro Springer London 2011-03-15, London, 2011. paperback. Condizione libro: New. Codice libro della libreria 9780857292988

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ISBN 10: 0857292986 ISBN 13: 9780857292988
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Descrizione libro Springer London Ltd, 2011. Condizione libro: New. 2011. 2011th Edition. Paperback. This accessible textbook supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. It provides study exercises at the end of each chapter, plus examples, definitions, theorems, and illustrations. Translator(s): Black, Nathanael T. Series: Undergraduate Topics in Computer Science. Num Pages: 328 pages, biography. BIC Classification: UYQ. Category: (P) Professional & Vocational. Dimension: 23 x 15 x 5. Weight in Grams: 496. . . . . . . Codice libro della libreria V9780857292988

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Descrizione libro Condizione libro: New. Depending on your location, this item may ship from the US or UK. Codice libro della libreria 97808572929880000000

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Descrizione libro Springer London Ltd. Paperback. Condizione libro: new. BRAND NEW, Introduction to Artificial Intelligence, Wolfgang Ertel, Nathanael T. Black, This concise and accessible textbook supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. The book presents concrete algorithms and applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks and reinforcement learning. Topics and features: presents an application-focused and hands-on approach to learning the subject; provides study exercises of varying degrees of difficulty at the end of each chapter, with solutions given at the end of the book; supports the text with highlighted examples, definitions, and theorems; includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning; contains an extensive bibliography for deeper reading on further topics; supplies additional teaching resources, including lecture slides and training data for learning algorithms, at an associated website. Codice libro della libreria B9780857292988

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Descrizione libro Springer London Ltd. Condizione libro: New. 2011. 2011th Edition. Paperback. This accessible textbook supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. It provides study exercises at the end of each chapter, plus examples, definitions, theorems, and illustrations. Translator(s): Black, Nathanael T. Series: Undergraduate Topics in Computer Science. Num Pages: 328 pages, biography. BIC Classification: UYQ. Category: (P) Professional & Vocational. Dimension: 23 x 15 x 5. Weight in Grams: 496. . . . . . Books ship from the US and Ireland. Codice libro della libreria V9780857292988

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Descrizione libro Springer London Ltd, 2011. PAP. Condizione libro: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Codice libro della libreria GB-9780857292988

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Descrizione libro Springer London Ltd, 2011. PAP. Condizione libro: New. New Book.Shipped from US within 10 to 14 business days.THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice libro della libreria IP-9780857292988

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