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Artificial Intelligence: A Modern Approach (2nd Edition) [Hardcover]

Stuart Russell , Peter Norvig
4.3 out of 5 stars  See all reviews (62 customer reviews)

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Book Description

December 30, 2002 0137903952 978-0137903955 2
For one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Click on "Features" tab below for more information Resources: Visit the author's website http://aima.cs.berkeley.edu/ to access both student and instructor resources including Power Point slides, syllabus. homework and exams, and solutions text problems.


Editorial Reviews

Review


"The publication of this textbook was a major step forward, not only for the teaching of AI, but for the unified view of the field that this book introduces. Even for experts in the field, there are important insights in almost every chapter." — Prof. Thomas Dietterich, Oregon State




"Just terrific. The book I've always been waiting for...the AI bible for the next decade." — Prof. Gerd Brewka (Vienna)




"A marvelous achievement, a truly beautiful book!" — Prof. Selmer Bringsjord, RPI




"It's a great book, with incredible breadth and depth, and very well-written. Everyone I know who has used it in their class has loved it." — Prof. Haym Hirsh, Rutgers




"I am deeply impressed by its unprecedented quality in presenting a coherent, balanced, broad and deep, enjoyable picture of the field of AI. It will become tire standard text for the years to come." — Prof. Wolfgang Bibel, Darmstadt




"Terrific! Well-written and well-organised, with comprehensive coverage of the material that every AI student should know." — Prof. Martha Pollack (Michigan)




"Outstanding ...Its descriptions are extremely clear and readable; its organization is excellent; its examples are motivating; and its coverage is scholarly and throughout! ...will deservedly dominate the field for some time." — Prof. Nils Nilsson, Stanford




"The best book available now...It's almost as good as the book Charniak and I wrote, but more up to date. (Okay I'll admit it, it may even be better than our book.)" — Prof. Drew McDermott, Yale




"A magisterial wide scope account of the entire field of Artificial Intelligence that will enlighten professors as well as students." — Dr. Alan Kay




"This is the book that made me love AI." — Student (Indonesia)


From the Back Cover

The first edition of Artificial Intelligence: A Modern Approach has become a classic in the AI literature. It has been adopted by over 600 universities in 60 countries, and has been praised as the definitive synthesis of the field.

In the second edition, 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.

The book is supported by a suite of online resources including source code, figures, lecture slides, a directory of over 800 links to "AI on the Web," and an online discussion group. All of this is available at:
aima.cs.berkeley.edu


Product Details

  • Hardcover: 1132 pages
  • Publisher: Prentice Hall; 2 edition (December 30, 2002)
  • Language: English
  • ISBN-10: 0137903952
  • ISBN-13: 978-0137903955
  • Product Dimensions: 10.1 x 8.2 x 1.7 inches
  • Shipping Weight: 4.8 pounds
  • Average Customer Review: 4.3 out of 5 stars  See all reviews (62 customer reviews)
  • Amazon Best Sellers Rank: #271,593 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews
50 of 51 people found the following review helpful
5.0 out of 5 stars Best Comprehensive text on AI November 22, 2005
Format:Hardcover
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.
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24 of 24 people found the following review helpful
5.0 out of 5 stars Give the Second Edition a Chance January 3, 2003
By A Customer
Format:Hardcover
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.
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43 of 50 people found the following review helpful
5.0 out of 5 stars Stunning textbook--best I've ever used February 9, 2005
Format:Hardcover|Verified Purchase
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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12 of 12 people found the following review helpful
5.0 out of 5 stars Rigorous view of AI January 31, 2005
Format:Hardcover
The book offers mathematically based coverage of the most important topics in AI. It has a very pragmatic view and does not spend too much time with the over-hyped topics, such as fuzzy logic, genetic algorithms. Instead, it provides clear and easy to understand examples for most of the introduced concepts.

The text requires some knowledge of computer science, mathematics, and statistics. Sections on topics that require extensive outside knowledge, such as computational learning theory, are not covered very deeply, but usually offer nice insight to the concepts and basic principles.

I recommend this book both for beginners to exact AI as an introductory text and to more experienced researchers as an invaluable reference. I found it to be the most useful book I own.
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16 of 18 people found the following review helpful
4.0 out of 5 stars An `ok' general purpose book on AI. March 7, 2005
By AlexS
Format:Hardcover
This is currently the best general purpose book on AI (the field). It is by no means the best book on any individual topic though... but I guess that wasn't the point of the book to begin with.

I'm not particularly happy with this book though. I think it's the language, or the examples, or something, but often it's just not `clear'---not as intuitive as I'd like. Many teachers seem to use it in a `general purpose course on AI' though (not anything particularly detailed, so it's `ok'---there are worse books on the subjects).

In short: as a general purpose AI book on everything, it does its job, but don't expect it to be anything other than a glorified field overview.
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8 of 8 people found the following review helpful
3.0 out of 5 stars Could have been great, but ... November 7, 2009
Format:Hardcover|Verified Purchase
As some reviewers have said, this is probably the most comprehensive AI textbook on the market. The "pros" of the book have been covered pretty well by other reviewers, so I'll limit my review to some of the things that bug me about the book.

1. No answer key for any problems. This feature has been standard in textbooks for decades as a way for students to self-check their understanding of the material.

2. Examples are scant and sometimes stop in the middle. For example, in Chapter 13, the example of applying Bayes' Rule gives one approach and indicates that it will discuss an alternative approach, but then the text just goes off on another path and never completes the example.

3. Inconsistent and (sometimes) convoluted pseudocode for the algorithms. Pseudocode should be a fairly-close-to-English approximation of the algorithm, but this book seems to mix RTL, English, and any other notation. Though the appendix includes an attempt at explaining their rationale behind their own brand of pseudocode, it's incomplete at best. Also, the function names don't follow any convention I've ever seen (I have 30+ years experience in software), and aren't even consistent within the book.

4. Condescending language. This should never occur in a textbook. In far too many places, the authors tell us that "the sharp-eyed reader will have noticed" or similar phrases, which basically implies, "if you didn't get our explanation and find the hidden subtext, you are not sharp-eyed". All such language should have been edited out.

The authors came so close to writing a classic, but sadly missed the mark. I think that any professors who claim that their students "universally love this book" are deluding themselves. Still, if your professor is good at explicating the material, it's worth going through it once, then switching to other materials, maybe primary source materials in the subfield(s) that grab your interest.
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Most Recent Customer Reviews
4.0 out of 5 stars Required Class Reading
A great deal of required reading. Text while being required, has a great level of depth on the subject matter. Read more
Published 10 months ago by masllc
5.0 out of 5 stars AI Introduction
I used this for a great class in AI. I learned some of the concepts that I struggled with in Discrete Math's predicate logic using this text. Read more
Published 16 months ago by Laura S. Nonamaker
5.0 out of 5 stars The Classic
This is the classic reference on Artificial Intelligence. I have read it mostly from cover to cover, and refer back to it often. Read more
Published 17 months ago by Dave
4.0 out of 5 stars Great explanations, good learning
I thought this book did a great job of explaining concepts and showing examples. Sometimes the examples could use a bit more explanation (especially for students from a discipline... Read more
Published 21 months ago by Matt
5.0 out of 5 stars Best Broadview AI Book
I have had this book for the past seven years and everytime some new problem comes up, there is something you can find related in this book! Read more
Published on June 6, 2012 by Subrat
5.0 out of 5 stars Great Broad AI Book
This book is a great survey of Artificial Intelligence that can be used to look back on no matter how experienced in the subject you become. Read more
Published on December 8, 2010 by Hudson T
3.0 out of 5 stars I Confess, I Wikipedia did a better job explaining some of the...
This was a decent book, but really, I felt the authors took a simple principle and DRAGGED it through the mud until it was no longer simple. Read more
Published on July 10, 2010 by Technogen
5.0 out of 5 stars Nice introductory text on AI
I used this book for a graduate course in Artificial Intelligence. We covered about half of the book in class. Read more
Published on August 23, 2009 by Siddhardha
4.0 out of 5 stars Probably the best known book on artificial intelligence
This is the text that was used in the Artificial Intelligence (AI) computer science course while I was an undergraduate. Read more
Published on December 30, 2008 by Alex Ferrugia
5.0 out of 5 stars Excellent Introductory Text
I have found this text to be a very readable introduction to the algorithms and methods used in intelligent agents. Read more
Published on December 9, 2008 by A. Borgman
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Hi John,

The term "software engineer" has become almost meaningless, so I'll answer in terms of undergraduate CS subjects. To get the most out of this book, you need to know undergrad data structures and algorithms (including basic complexity theory), logic and proofs, basic... Read More
Jul 3, 2006 by Chris Simpkins |  See all 2 posts
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