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Science/Engineering Statistical Mechanics, Third Edition
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Science/Engineering Knowledge Representation and Reasoning (The Morgan Kaufmann Series in Artificial Intelligence)
Posted on 2010-03-15
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Knowledge Representation and Reasoning (The Morgan Kaufmann Series in Artificial Intelligence) (The Morgan Kaufmann Series in Artificial Intelligence) By Ronald Brachman, Hector Levesque, Publisher: Morgan Kaufmann
Number Of Pages: 381 Publication Date: 2004-05-19 Sales Rank: 248007 ISBN / ASIN: 1558609326 EAN: 9781558609327 Binding: Hardcover Manufacturer: Morgan Kaufmann Studio: Morgan Kaufmann Average Rating: 4.5 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 Review: how to reason about knowledge Brachman and Levesque describe what may be considered the foundations of artificial intelligence. They look at how to represent knowledge. As far more than just a passive collection of facts. The "Reasoning" in the book's title is the important aspect of that representation. You can understand how to apply reasoning in a logical and systematic manner. Those of you from a computing background may also find similarities between the discussion of object oriented representations and various OO programming languages. You might actually key off these similarities by using the text to guide your KR coding. Date: 2005-06-24 Rating: 5 Review: Don't have to be a math buff to understand I came across this book looking for a text that would explain the context of First Order Logic, why it is used for so many knowledge representation problems, how it is used to solve them, and its limitations. I must say that this is far and away the best book I've found to answer these questions. If you search around a little at the competition, you will find much of the text quickly turning to mathematical proofs and deductions in their explanations. While this is of course necessary and helpful, it doesn't (for me) really give an idea of how and why these methods are used practically. You can tell that these authors spent some time on ensuring consistency and fluency of the writing, which I find so very helpful. I'm trying to think of something bad to say about it: I wish it were longer! If you read the preface you will see the authors call it an introduction, which is definitely true. Maybe they will team up again for a more in-depth text on some aspect of this subject.Password: gigapedia.org
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