Examines the central concepts of knowledge representation. This book presents the various styles of representation and explains the basics of reasoning with that representation. It is suitable for researchers and practitioners in database management, information retrieval, and object-oriented systems as well as artificial intelligence. Series: The Morgan Kaufmann Series in Artificial Intelligence. Num Pages: 381 pages, Illustrated. BIC Classification: UYQE. Category: (P) Professional & Vocational. Dimension: 240 x 198 x 28. Weight in Grams: 830. . 2004. 1st Edition. Hardcover. . . . .

N� de ref. del art�culo V9781558609327

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Detalles bibliogr�ficos

T�tulo: Knowledge, Representation and Reasoning
Editor: Elsevier Science & Technology
Fecha de publicaci�n: 2004
Idioma: Ingl�s
ISBN 10: 1558609326
ISBN 13: 9781558609327
Encuadernaci�n: Encuadernaci�n de tapa dura
Edici�n: 1� Edici�n
Estado: New

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Sinopsis

Knowledge representation is at the very core of a radical idea for understanding intelligence. Instead of trying to understand or build brains from the bottom up, its goal is to understand and build intelligent behavior from the top down, putting the focus on what an agent needs to know in order to behave intelligently, how this knowledge can be represented symbolically, and how automated reasoning procedures can make this knowledge available as needed. This landmark text takes the central concepts of knowledge representation developed over the last 50 years and illustrates them in a lucid and compelling way. Each of the various styles of representation is presented in a simple and intuitive form, and the basics of reasoning with that representation are explained in detail. This approach gives readers a solid foundation for understanding the more advanced work found in the research literature. The presentation is clear enough to be accessible to a broad audience, including researchers and practitioners in database management, information retrieval, and object-oriented systems as well as artificial intelligence. This book provides the foundation in knowledge representation and reasoning that every AI practitioner needs.

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By Dr. Ronald Brachman and Hector Levesque

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