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Knowledge Representation and Reasoning

Knowledge Representation and Reasoning

Ronald J. Brachman, Hector J. Levesque
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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.

• Authors are well-recognized experts in the field who have applied the techniques to real-world problems

• Presents the core ideas of KR&R in a simple straight forward approach, independent of the quirks of research systems

• Offers the first true synthesis of the field in over a decade

种类:
年:
2004
出版:
1st
出版社:
Morgan Kaufmann
语言:
english
页:
381
ISBN 10:
1558609326
ISBN 13:
9781558609327
系列:
The Morgan Kaufmann Series in Artificial Intelligence
文件:
PDF, 2.29 MB
IPFS:
CID , CID Blake2b
english, 2004
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