Artificial Intelligence: A Modern Approach (Pearson Series in Artifical Intelligence) Hardcover – 17 Nov. 2020

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.

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.

Bought for my son who is in year 2 of a MSC in Computer Science with AI. He doesn’t read books. Ever. So what was I thinking giving him a book with over 1100 pages? Well, early days, but so far he has been lounging on the sofa every spare minute—reading!! He loves it.As an engineer with zero knowledge of AI, I browsed the book and found the writing style easy to read and yet very precise and concise. The chapter intros are easy to understand, the detail in the later chapters goes completely over my head, which is probably a very good thing.

The most complete and well explained book that you can find for AI 2020 and probably following year.I didn't read the 3rd edition, I'm just starting in the field and decided to take the 4th edition from the market. No regrets.

Unreadable on Kindle for Mac. Unreadable on Cloud reader. In summary unreadable. Thinking of asking for my money back.