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Artificial Intelligence: A Modern Approach
By Stuart J. Russell and Peter Norvig
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Hardcover
Book cover for 9780131038059 Book cover for 9780136042594 Book cover for 9780137903955
 
3 edition from Prentice Hall (December 1, 2009)
9780136042594 | details & prices | 1132 pages | 8.50 × 10.25 × 1.75 in. | 4.75 lbs | List price $151.00
About: Artificial Intelligence: A Modern Approach, 3e offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence.
2 edition from Prentice Hall (December 1, 2002)
9780137903955 | details & prices | 1080 pages | 8.00 × 10.00 × 1.75 in. | 4.75 lbs | List price $132.00
About: Presents a guide to artificial intelligence, covering such topics as intelligent agents, problem-solving, logical agents, planning, uncertainty, learning, and robotics.
The price comparison is for this edition
from Prentice Hall (February 1, 1995)
9780131038059 | details & prices | 8.00 × 9.50 × 1.75 in. | 3.65 lbs | List price $84.00
About: This is an introduction to the theory and practice of artificial intelligence.
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Publisher Prentice Hall
Publication date February 1, 1995
Binding Hardcover
Book category Adult Non-Fiction
ISBN-13 9780131038059
ISBN-10 0131038052
Dimensions 1.75 by 8 by 9.50 in.
Weight 3.65 lbs.
Original list price $84.00
Amazon.com says people who bought this book also bought:
Paradigms of Artificial Intelligence Programming | Artificial Intelligence | Artificial Intelligence | Computer Networking | Introduction to Algorithms
(view table of contents)
Amazon.com description: Product Description: This is an introduction to the theory and practice of artificial intelligence. It uses an intelligent agent as the unifying theme throughout, and covers areas that are sometimes underemphasized elsewhere. These include reasoning under uncertainty, learning, natural language, vision and robotics. The book also explains in detail some of the more recent ideas in the field, including simulated annealing, memory-bounded search, global ontologies, dynamic belief networks, neural nets, inductive logic programming, computational learning theory, and reinforcement learning.

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