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Artificial Intelligence: A Modern Approach Hardcover – April 28 2020

by Stuart Russell (Author), Peter Norvig (Author)
4.6 4.6 out of 5 stars 403 ratings
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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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  1. ISBN-10
    0134610997
  2. ISBN-13
    978-0134610993
  3. Edition
    4th
  4. Publisher
    Pearson
  5. Publication date
    April 28 2020
  6. Part of series
    Pearson Series in Artifical Intelligence
  7. Language
    English
  8. Dimensions
    21.34 x 4.32 x 25.65 cm
  9. Print length
    1136 pages
  10. See all details
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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 ‏ : ‎ 100 g
  • Dimensions ‏ : ‎ 21.34 x 4.32 x 25.65 cm
  • Customer Reviews:
    4.6 4.6 out of 5 stars 403 ratings

About the author

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Stuart Russell

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
403 global ratings

Top reviews from Canada

zulban
5.0 out of 5 stars best textbook I've found so far
Reviewed in Canada on June 22, 2023
Verified Purchase
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.
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Rhonald M.
5.0 out of 5 stars Excellent book for the ones who are strong in math and know the foundation
Reviewed in Canada on January 25, 2021
Verified Purchase
This must be used as a book for the computer science students of the AI masters who are already experienced but want to deep dive into many concepts to improve their thinking. After going through seven chapters, trying to solve some of them, I switched to a much simpler book. Now that I understand many basics, I am planning to revisit them. This book, along with The Art of Computer Programming, is an investment.
One person found this helpful
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Pierre Andre Chery
5.0 out of 5 stars Repond conformement à mes attentes.
Reviewed in Canada on December 1, 2021
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Excellente book . love it!
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Christophe Pere
5.0 out of 5 stars Best book in AI world
Reviewed in Canada on February 28, 2021
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The “bible” of AI covers lots of subjects and domains. The price is expensive but it worth it.
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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
Verified Purchase
This book is HUGE. At 1100 pages, it's an exercise just to hold it and flip through it. The pages are thin but in full color. Everything you wanted to know (and didn't know you wanted to know) about AI is here.

The book focuses on AI, and uses pseudocode for almost every coding example, without getting bogged down in programming language specific details like most textbooks do.

The book covers beginner, intermediate, and advanced topics. (Not that there really is a "beginner" level to the subject of AI.) This is probably the most comprehensive book ever written on the subject, and there's enough material here for two semesters worth of study at least.

My biggest complaint is that there are no exercise questions in the book. Everything is online, the website is poorly maintained with duplicate questions everywhere, is not consistent with the chapters in the book, and has no solutions available to any of the questions. Having exercise questions helps to reinforce the material being learned. Providing solutions (or at least offering a solutions manual for purchase) is vital to guide understanding.

This is the standard text used in software engineering programs in Canada (and elsewhere) for learning about AI.
2 people found this helpful
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Ivan
5.0 out of 5 stars Great book.
Reviewed in Canada on September 23, 2021
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As described.
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MEET PANDYA
5.0 out of 5 stars Worth it!
Reviewed in Canada on August 15, 2020
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Very well written
One person found this helpful
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M.J. A
2.0 out of 5 stars Poor quality print job
Reviewed in Canada on May 29, 2022
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Every CompSci maj knows where to get the pdf. I wanted a quality physical text and paid $200 but this has many warped pages on day 1, similar to water damage . Poor quality print
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Top reviews from other countries

Translate all reviews to English
Adriana Morales
5.0 out of 5 stars Buen referente de inteligencia artificial
Reviewed in Mexico on September 22, 2023
Verified Purchase
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
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Richard Irving
5.0 out of 5 stars Exceptionally well written - balancing the theoretical and practical
Reviewed in the United States on August 4, 2022
Verified Purchase
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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Rafael
5.0 out of 5 stars Excelente
Reviewed in Brazil on November 10, 2021
Verified Purchase
Livro completo. Muito denso e técnico, mas de grande valia e de uma qualidade sensacional.
4 people found this helpful
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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
Verified Purchase
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
Verified Purchase
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)
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One person found this helpful
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