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


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The most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence
The long-anticipated revision of
Artificial Intelligence: A Modern Approach explores the full breadth and depth of the field of artificial intelligence (AI). The 4th Edition brings readers up to date on the latest technologies, presents concepts in a more unified manner, and offers new or expanded coverage of machine learning, deep learning, transfer learning, multiagent systems, robotics, natural language processing, causality, probabilistic programming, privacy, fairness, and safe AI.


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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.

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:

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Stuart Russell
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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.

Customer reviews

4.6 out of 5 stars
4.6 out of 5
420 global ratings
The content is great, the printing quality is moderate
4 Stars
The content is great, the printing quality is moderate
The content is great, but the printing quality is moderate.Also such an expensive book was slightly damaged during delivery because of poorly packaging and careless delivery.
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Top reviews from the United States

Reviewed in the United States on August 4, 2022
Very clearly written with all arguments straightforwardly expressed. I found it most helpful to cover in detail what we mean by intelligence/thought/capability before diving into the mechanics. Also the authors are honest about what is not known, including why certain methods work better than others.
5 people found this helpful
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Reviewed in the United States on January 13, 2021
- I liked the structure of the book in terms of content and printing format.
- I did not like the binding; although it is hardcover (which I prefer over paperback), it is glued like a paperback, and I am concerned the pages may start coming apart.
- I would have liked some examples within the text, as well as exercises (along with solutions in a separate instructor's manual).
4 people found this helpful
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Reviewed in the United States on April 15, 2022
This book is definitely an improvement on last version which was already amazing. Very recommended
2 people found this helpful
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Reviewed in the United States on March 12, 2021
George Polya, the mathematician, once wrote: "If you can't solve a problem, then there is an easier problem you can solve. Find it". This book helps you find the easier problem. This is the greatest complement I could give to any technical book.
4 people found this helpful
Report
Reviewed in the United States on February 12, 2021
Has everything a beginner needs to know and master AI. Also easy to read and understand. Finally the author has created a website for this book where implementation of real life AI problems are written in java, python and various other languages.
2 people found this helpful
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Reviewed in the United States on November 20, 2020
I like that this book covers a lot of ground and provides super useful information and algorithms. Super great book.

I don't like that some parts in the algorithm pseudo code aren't thoroughly explained with examples of usage. Also, the formulae notation for the i'th and j'th iteration characters aren't properly explained or consistent across formulae, making it more difficult for beginners. I think the formulae notations could be more consistent and thoroughly explained.
7 people found this helpful
Report
Reviewed in the United States on June 10, 2022
Education,excelent book !
Reviewed in the United States on March 9, 2022
good

Top reviews from other countries

Adriana Morales
5.0 out of 5 stars Buen referente de inteligencia artificial
Reviewed in Mexico on September 22, 2023
Si se quiere empezar a aprender Inteligencia Artificial, este es el camino de entrada, es importante tener buenos fundamentos de programación, estructuras de datos y algoritmos
zulban
5.0 out of 5 stars best textbook I've found so far
Reviewed in Canada on June 22, 2023
This is the highest quality textbook content I've ever seen in any textbook. I'm a huge AI enthusiast and wanted a high quality textbook to read cover to cover. Was worried about the price but it turned out to be worth it.
Rafael
5.0 out of 5 stars Excelente
Reviewed in Brazil on November 10, 2021
Livro completo. Muito denso e técnico, mas de grande valia e de uma qualidade sensacional.
4 people found this helpful
Report
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
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.
Customer image
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
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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5 people 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
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)
Customer image
Jaume
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)
Images in this review
Customer image
Customer image
One person found this helpful
Report