Knowledge Representation and Reasoning

by Ronald J. Brachman, Hector J. Levesque

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.

Genres: Computers, Reference, Philosophy, Textbooks, Artificial Intelligence, Mathematics

416 pages, Hardcover

First published February 18, 1992

Reviews

[Snow · Rating 3 out of 5]

I would have liked to have less logic and more pure explanation of what exactly each element does.

[Paul]

One thing to note when reading is that they use the horseshoe "⊃" symbol instead of the directed arrow "→" to represent implication. I guess this is syntactically valid, but confused me for a while.

[Braga Basil · Rating 4 out of 5]

Good enough for a general understanding, but you need to dig more for specifics.

[Hanna Abi Akl · Rating 5 out of 5]

An excellent primer on all things knowledge representation, reasoning mechanisms and plenty of exercises on the more challenging topics introduced in this book.

[Dewi Wardani]

it's close to a general logic in artificial intelligent. good point it's all I needed..but i like it also more elaborate some use cases ... ;)