9781558609327-1558609326-Knowledge Representation and Reasoning (The Morgan Kaufmann Series in Artificial Intelligence)

Knowledge Representation and Reasoning (The Morgan Kaufmann Series in Artificial Intelligence)

ISBN-13: 9781558609327
ISBN-10: 1558609326
Edition: 1
Author: Ronald Brachman, Hector Levesque
Publication date: 2004
Publisher: Morgan Kaufmann
Format: Hardcover 416 pages
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Book details

ISBN-13: 9781558609327
ISBN-10: 1558609326
Edition: 1
Author: Ronald Brachman, Hector Levesque
Publication date: 2004
Publisher: Morgan Kaufmann
Format: Hardcover 416 pages

Summary

Knowledge Representation and Reasoning (The Morgan Kaufmann Series in Artificial Intelligence) (ISBN-13: 9781558609327 and ISBN-10: 1558609326), written by authors Ronald Brachman, Hector Levesque, was published by Morgan Kaufmann in 2004. With an overall rating of 4.4 stars, it's a notable title among other AI & Machine Learning (Software, Computer Science) books. You can easily purchase or rent Knowledge Representation and Reasoning (The Morgan Kaufmann Series in Artificial Intelligence) (Hardcover) from BooksRun, along with many other new and used AI & Machine Learning books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $12.72.

Description

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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