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Artificial Intelligence: A Modern Approach (Pearson Series in Artifical Intelligence) 4th Edition

4.6 out of 5 stars 375 ratings

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Editorial Reviews

About the Author

About our authors

Stuart Russell was born in 1962 in Portsmouth, England. He received his B.A. with first-class honours in physics from Oxford University in 1982, and his Ph.D. in computer science from Stanford in 1986. He then joined the faculty of the University of California at Berkeley, where he is a professor and former chair of computer science, director of the Center for Human-Compatible AI, and holder of the Smith–Zadeh Chair in Engineering. In 1990, he received the Presidential Young Investigator Award of the National Science Foundation, and in 1995 he was co-winner of the Computers and Thought Award. He is a Fellow of the American Association for Artificial Intelligence, the Association for Computing Machinery, and the American Association for the Advancement of Science, and Honorary Fellow of Wadham College, Oxford, and an Andrew Carnegie Fellow. He held the Chaire Blaise Pascal in Paris from 2012 to 2014. He has published over 300 papers on a wide range of topics in artificial intelligence. His other books include: The Use of Knowledge in Analogy and Induction, Do the Right Thing: Studies in Limited Rationality (with Eric Wefald), and Human Compatible: Artificial Intelligence and the Problem of Control.

Peter Norvig is currently Director of Research at Google, Inc., and was the director responsible for the core Web search algorithms from 2002 to 2005. He is a Fellow of the American Association for Artificial Intelligence and the Association for Computing Machinery. Previously, he was head of the Computational Sciences Division at NASA Ames Research Center, where he oversaw NASA’s research and development in artificial intelligence and robotics, and chief scientist at Junglee, where he helped develop one of the first Internet information extraction services. He received a B.S. in applied mathematics from Brown University and a Ph.D. in computer science from the University of California at Berkeley. He received the Distinguished Alumni and Engineering Innovation awards from Berkeley and the Exceptional Achievement Medal from NASA. He has been a professor at the University of Southern California and a research faculty member at Berkeley. His other books are: Paradigms of AI Programming: Case Studies in Common Lisp, Verbmobil: A Translation System for Face-to-Face Dialog, and Intelligent Help Systems for UNIX.

The two authors shared the inaugural AAAI/EAAI Outstanding Educator award in 2016.


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Product details

  • Publisher ‏ : ‎ Pearson; 4th edition (April 28, 2020)
  • Language ‏ : ‎ English
  • Hardcover ‏ : ‎ 1136 pages
  • ISBN-10 ‏ : ‎ 0134610997
  • ISBN-13 ‏ : ‎ 978-0134610993
  • Item Weight ‏ : ‎ 3.53 ounces
  • Dimensions ‏ : ‎ 8.4 x 1.7 x 10.1 inches
  • Customer Reviews:
    4.6 out of 5 stars 375 ratings

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Stuart Russell is a professor of Computer Science and holder of the Smith-Zadeh Chair in Engineering at the University of California, Berkeley, where he also directs the Center for Human Compatible Artificial Intelligence. He is an Honorary Fellow of Wadham College, University of Oxford and the vice-chair of the World Economic Forum's Council on AI and Robotics. His work for the UN building a new global seismic monitoring system for the Comprehensive Nuclear-Test-Ban Treaty has been recognized by the Feigenbaum Prize of the Association for the Advancement of Artificial Intelligence. He has been an invited speaker at TED, the World Economic Forum, and the Nobel Dialogues in Stockholm and Tokyo. He is the author (with Peter Norvig) of Artificial Intelligence: A Modern Approach, the number one bestselling textbook in AI which is used in over 1,400 universities in 128 countries. He was born in England and lives in Berkeley and Paris.

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4.6 out of 5 stars
4.6 out of 5
375 global ratings

Top reviews from the United States

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Reviewed in the United States 🇺🇸 on August 4, 2022
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Reviewed in the United States 🇺🇸 on August 22, 2022
Reviewed in the United States 🇺🇸 on May 26, 2020
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5.0 out of 5 stars Everything I was hoping for!
By Thomas J Ballatore on May 25, 2020
While I loved the 3rd edition of this book, I've been looking forward for years for this update to *the* leading AI textbook. I was giddy when unboxing this and so far it hasn't disappointed.

Clarifications. (1) It's actually a hardcover. The amazon description says "Paperback: 1136 pages" but, as expected, it's a well-bound hardcover. (2) Another reviewer noted that the print is very light. In my copy, the print is just fine but I did notice that the pages are quite thin. They seem sturdy but are relatively transparent...I assume this is a simple tradeoff—they want to pack the 1100+ pages into a reasonable size and weight. Overall, it feels great to hold and flip through.

Observations. (1) It's in color! I wasn't expecting that but it makes sense given the addition of many more images, esp. on computer vision. (2) I skipped straight to Chapter 21 on Deep Learning, authored by Ian Goodfellow. Overall, they must have a great editor because the tone and style match well the "Russell/Norvig style" you might be used to from previous editions. I assume the other guest-written chapters are the same. (3) It's not cheap but I'd expect it to hold value for many years as it's unlikely to be updated for ~10 years and there will be significant demand for used copies if you decided to resell. (4) Minor point but I like the smell—it's definitely a real book!

Overall, if you are interested in AI and want the most comprehensive overview, buy now!

P.S. Well done adding Ada Lovelace to the already though-provoking cover.
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Reviewed in the United States 🇺🇸 on July 12, 2022
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3.0 out of 5 stars Mal empaque, tengo 3 paginas dañadas
By Sebastian on July 12, 2022
El libro llegó en general bien a excepción de 3 paginas que debido al mal embalaje sufrieron daños
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Reviewed in the United States 🇺🇸 on June 10, 2022
Reviewed in the United States 🇺🇸 on April 15, 2022
Reviewed in the United States 🇺🇸 on November 20, 2020
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Reviewed in the United States 🇺🇸 on March 9, 2022

Top reviews from other countries

Ben
5.0 out of 5 stars Worth getting the 4th Edition
Reviewed in the United Kingdom 🇬🇧 on August 17, 2020
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5.0 out of 5 stars Worth getting the 4th Edition
Reviewed in the United Kingdom 🇬🇧 on August 17, 2020
I ordered a copy to the UK from Amazon US. Presumably, an international edition will become available but I can't find one at time of writing (Aug 2020).

The copy I received appears genuine but arrived with a printing defect on the title page, which was irritating given it cost £135. The pages are not bad quality but are thin enough you can see the text on the other side pretty clearly. I guess this is reasonable given the book has a little over a thousand pages. It is printed in full-colour.

Right now the 4th edition (2020) is significantly more expensive than the 3rd. I recommend spending the extra money. The 3rd edition is from 2010 and the 4th isn't just minor changes - To quote the book:

"Overall, about 25% of the material in the book is brand new. The remaining 75% has been largely re-written to present a more unified picture of the field. 22% of the citations in this edition are to works published after 2010."

As the book is a classic and seems to be the most commonly recommended textbook for this field I won't spend long trying to sell you on the content - it's excellent as expected. So far my impression is it's extremely well written, well-edited and vast in scope.

A criticism I saw levelled at the third edition was that it was difficult to use as a reference due to a lack of detail in the Contents and badly executed Index. This appears to have been corrected for the 4th ed. The Contents explains each chapter to a good level of detail. The Index and Bibliography appear comprehensive.

I'm very happy with the purchase and sure it will be a valuable reference throughout studying a Machine Learning/AI related masters.
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Ben Fraser
5.0 out of 5 stars The definitive and most comprehensive book on Artificial Intelligence.
Reviewed in the United Kingdom 🇬🇧 on May 22, 2021
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5.0 out of 5 stars The definitive and most comprehensive book on Artificial Intelligence.
Reviewed in the United Kingdom 🇬🇧 on May 22, 2021
For anyone who has studied the previous version(s) of this book, you'll know just how detailed and incredibly comprehensive this is. It is generally agreed to be the most credible and thorough book within the field of AI, by virtue of the backgrounds of the primary authors, along with its vast size of 1100+ pages. Even at this vast length, the information distilled into each of the sections is dense and very valuable, and I cant really highlight any chapters that are particularly redundant. You can also gain an incredible amount of knowledge from each of the sections of the book, even without a full understanding of the concepts the first time round (or reading many of the earlier chapters). For this reason it is widely used as a primary reference throughout academic courses in AI.

Where this book really shines is its heavy focus on foundational AI principles and topics that are concrete and timeless (as timeless as concepts can be in such a fast-moving field!). The modernised field of AI is heavily dominated by machine learning, but this represents only a subset of the field, with a vast expanse of other important subfields. This book branches across into all of these other areas (along with strong coverage of machine learning too), and if studied, will provide you with a very strong and grounded foundation in AI.

It should be highlighted that the book is challenging, and is far from a simple read. It is very good as a reference book, and for dipping into and out of as required - it's unlikely you'll manage to commit to reading the book from start to finish. This is not due to fault of the authors, who do a fantastic job of using engaging and easily-read writing styles, but is simply by virtue of the complicated and vast topics that the book is based on.

In terms of the 4th Edition itself, I would fully recommend this updated version over any of the previous versions. There is a significant amount of new material and improvements compared to the 3rd edition, which helps capture the major developments throughout the past ten years. There are now extensive chapters on Deep learning, probabilistic programming, multi-agent architectures, natural language processing, computer vision and robotics. Furthermore, the book now has a much better glossary with huge range of topics to quickly find, which was definitely a downside of prior editions.

In terms of the physical book itself, I have no major issues with the 4th Edition and can summarise as follows:
- It is huge (1100+ pages).
- It is expensive, but nevertheless a very good investment. It is unlikely another edition of this book will be released for a long time (last version was published in 2010), and so this will stand the test of time for now.
- High quality hardback, with good binding (contrary to other reviews I have read).
- The pages are thin, but nevertheless high quality, with great use of colour on all pages, illustrations and diagrams.
- The book shipped from the US to the UK for delivery, and despite this still arrived pristine without any damage at all. I ordered through Amazon with Book Depository, who packaged it very carefully in a decent sized box with bubble wrap. I know some other sellers might not be so diligent, which isn't worth taking the chance with such an expensive book.

Overall, I thoroughly recommend. An essential book for the collection of any AI researchers, students, data scientists or AI practitioners.
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2 people found this helpful
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T. Gerhardt
5.0 out of 5 stars Deeply technical and yet compelling reading.
Reviewed in the United Kingdom 🇬🇧 on February 14, 2021
One person found this helpful
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Jaume
5.0 out of 5 stars El mejor libro de texto sobre inteligencia artificial
Reviewed in Spain 🇪🇸 on March 22, 2021
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5.0 out of 5 stars El mejor libro de texto sobre inteligencia artificial
Reviewed in Spain 🇪🇸 on March 22, 2021
Este libro ha sufrido varias reediciones, pero la edición 2020 es simplemente soberbia, es un tratado completo de todas las áreas de la Inteligencia Artificial, completamente actualizada.
Los capítulos de Machine Learning y Deep Learning han sido actualizados de forma que incluyen los últimos avances, y al verificar los autores de cada capítulo se observa que los principales investigadores de cada área han colaborado.
Es un libro de texto que da para varias asignaturas trimestrales, y como consulta tiene un valor incalculable.
Lo recomiendo a todo estudiante avanzado de informática o matemáticas que quiera entrar en el mundo fascinante de la IA.
Ojo. Es un libro de texto, pesa un par de kilos (revisa las medidas porque es un libro grande)
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Chris Baehr
4.0 out of 5 stars Makes other textbooks look tiny. Standard text for software engineering
Reviewed in Canada 🇨🇦 on March 16, 2021
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