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Artificial Intelligence: A Modern Approach (2nd Edition) (Prentice Hall Series in Artificial Intelligence)

Artificial Intelligence: A Modern Approach (2nd Edition) (Prentice Hall Series in Artificial Intelligence)

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Authors: Stuart Russell, Peter Norvig
Publisher: Prentice Hall
Category: Book

List Price: $123.00
Buy New: $85.23
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New (36) Used (20) from $58.99

Rating: 4.0 out of 5 stars 84 reviews
Sales Rank: 1939

Media: Hardcover
Edition: 2
Pages: 1132
Number Of Items: 1
Shipping Weight (lbs): 4.8
Dimensions (in): 10.1 x 8.2 x 1.7

ISBN: 0137903952
Dewey Decimal Number: 006.3
EAN: 9780137903955

Publication Date: December 30, 2002
Availability: Usually ships in 24 hours

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Editorial Reviews:

Amazon.com Review
Artificial Intelligence: A Modern Approach introduces basic ideas in artificial intelligence from the perspective of building intelligent agents, which the authors define as "anything that can be viewed as perceiving its environment through sensors and acting upon the environment through effectors." This textbook is up-to-date and is organized using the latest principles of good textbook design. It includes historical notes at the end of every chapter, exercises, margin notes, a bibliography, and a competent index. Artificial Intelligence: A Modern Approach covers a wide array of material, including first-order logic, game playing, knowledge representation, planning, and reinforcement learning.

Product Description
The long-anticipated revision of this best-selling book offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Intelligent Agents. Solving Problems by Searching. Informed Search Methods. Game Playing. Agents that Reason Logically. First-order Logic. Building a Knowledge Base. Inference in First-Order Logic. Logical Reasoning Systems. Practical Planning. Planning and Acting. Uncertainty. Probabilistic Reasoning Systems. Making Simple Decisions. Making Complex Decisions. Learning from Observations. Learning with Neural Networks. Reinforcement Learning. Knowledge in Learning. Agents that Communicate. Practical Communication in English. Perception. Robotics. For those interested in artificial intelligence.


Customer Reviews:   Read 79 more reviews...

5 out of 5 stars Second Edition has been published!   January 9, 2003
Stuart Russell (Berkeley, CA USA)
28 out of 29 found this review helpful

Thanks to all those who reviewed the first edition.
If you are reading this, you will probably want the
second edition instead. It was published Dec 20, 2002.
Every chapter has been extensively rewritten.
Significant new material has been introduced to cover
areas such as constraint satisfaction, fast propositional
inference, planning graphs, internet agents, exact
probabilistic inference, Markov Chain Monte Carlo
techniques, Kalman filters, ensemble learning methods,
statistical learning, probabilistic natural language
models, probabilistic robotics, and ethical aspects of AI.

For more information, see aima.cs.berkeley.edu


5 out of 5 stars Best Comprehensive text on AI   November 22, 2005
calvinnme (Fredericksburg, Va)
26 out of 27 found this review helpful

I didn't think that the first edition of this book was as bad as some of the reviewers said, but the second edition is definitely a vast improvement. It's not just some obligatory 2nd edition that some authors release to say that they are staying actively published. The first edition was somewhat confusing in its explanations and the exercises were really blurry on what was being asked. All of that has now been resolved.
The book is a comprehensive and insightful introduction to artificial intelligence with an academic tone. It provides a unified view of the field organized around the rational decision making paradigm, which focuses on the selection of the "best" solution to a problem. The book's overall theme is that the purpose of AI is to solve problems via intelligent agents, and then goes about specifying the features such an agent or agents should have. Pseudocode is provided for all of the major AI algorithms. Being about the broadest book in terms of coverage of AI, you should therefore not expect it to be the deepest in coverage. However, each topic is covered to the extent that the reader should understand its essence. Sections one through six are absolutely wonderful, and comprise the "meat" of AI. Section seven is rather weak since it tries to cover both robotics and text processing in their own individual chapters, and entire books have a hard time covering this material. Section eight is different from the others, since it talks about the philosophy and future of AI.
Another plus for this book is that there is a great deal of extra material that deals with standard AI curriculum. For example, the chapters on logic not only include the typical introduction to propositional and first order logic together with the usual inference procedures, they also give many useful hints how to use first order logic to actually represent aspects of the real world such as measures, time, actions, mental objects, etc. These chapters also contain much information about how to implement efficient logical reasoners.
Finally, this second edition has an excellent website that can be found by going through the publisher's webpage for the book. This website contains four sample chapters, pseudocode, and actual code in Java, Python, and LISP.
I notice that Amazon shows the table of contents from the first edition, so I am showing what the actual table of contents is for the second edition for the purpose of completeness. Note that the book has been significantly reorganized.
I. ARTIFICIAL INTELLIGENCE.
1. Introduction.
2. Intelligent Agents.
II. PROBLEM-SOLVING.
3. Solving Problems by Searching.
4. Informed Search and Exploration.
5. Constraint Satisfaction Problems.
6. Adversarial Search.
III. KNOWLEDGE AND REASONING.
7. Logical Agents.
8. First-Order Logic.
9. Inference in First-Order Logic.
10. Knowledge Representation.
IV. PLANNING.
11. Planning.
12. Planning and Acting in the Real World.
V. UNCERTAIN KNOWLEDGE AND REASONING.
13. Uncertainty.
14. Probabilistic Reasoning Systems.
15. Probabilistic Reasoning Over Time.
16. Making Simple Decisions.
17. Making Complex Decisions.
VI. LEARNING.
18. Learning from Observations.
19. Knowledge in Learning.
20. Statistical Learning Methods.
21. Reinforcement Learning.
VII. COMMUNICATING, PERCEIVING, AND ACTING.
22. Agents that Communicate.
23. Text Processing in the Large.
24. Perception.
25. Robotics.
VIII. CONCLUSIONS.
26. Philosophical Foundations.
27. AI: Present and Future.



5 out of 5 stars Give the Second Edition a Chance   January 3, 2003
16 out of 16 found this review helpful

Most of the reviews here refer to the first edition, not the second. There have been significant changes to the second edition. Amazon should consider using a display that clarifies which edition each review refers to.


5 out of 5 stars A Review of Russell and Norvig's AI: A Modern Approach   February 16, 2001
Robert Jones (Emporia, Kansas USA)
23 out of 25 found this review helpful

Russell and Norvig's AI: A Modern Approach is THE best AI text out there. At 932 pages it is encyclopedic, it has nearly everything. So what is missing? How could it be improved? Probably the worst thing about the book is the binding. I am not sure that you can read it from cover to cover without some pages coming loose. Perhaps its the length. Perhaps it needs to be split into two volumes. I am not a fan of pseudocode and all the algorithms are in pseudocode. I think the right compromise between detailed practical code and tutorial compactness is something like the code in Jackson's text Expert Systems. I realize this might make a long book even longer but I still think some examples in Lisp, Prolog, etc. would be an improvement. There are a few things missing. Some detail on case-based reasoning is needed and some newer topics like hybrid systems and rough sets. Also, more on parallel computing for AI. Occasionally I was annoyed by the references. On page 27 the authors attribute a story to Heckerman's 1991 thesis. The thesis contains no such story. The reference should have been to a private communication. By now you might think I hate the book. No. I am suggesting improvements. I repeat. It is THE BEST SINGLE AI TEXT IN PRINT. But you will not be able to teach the whole book in a single AI course. Not even a two semester course.


5 out of 5 stars Stunning textbook--best I've ever used   February 9, 2005
R. Johnson (Sweet Home Chicago)
43 out of 50 found this review helpful

Until recently, my Algorithms book was my favorite text book ever. However, AI: A Modern Approach has supplanted it. This book is the most thoughtfully designed, easily understandable, clear text I've ever used in over 28 years of attending schools. I really knew nothing about AI when I took my first grad class in AI, but this book, along with a pretty great instructor, has been a wonderful resource, more than any other book I've used. I have not need to google for more information or speak to the professor. The answers are here--clear and concrete.

Have no fear and trust this book!


 
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