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on 2 November 2006
This is my favourite AI textbook, which I strongly recommend. But be warned: it's long and detailed and thorough, so don't expect a lightweight overview - it's where to go when you really want to understand the stuff. It's heavily biased towards First Order Logic as the way to do knowledge representation, and is especially good on Bayesian networks.

If you're interested in the philosophical issues involved in "real artificial intelligence" rather than (or as well as) the technical stuff, chapter 26 is a superb introduction.
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on 6 October 2000
This book is a great general AI book. Its covers all topics that are associated with AI today and goes into some depth with all of them. It can be used as a intoduction or as a useful refernce book. I bought this book out of curiosity and it has encouraged me to find out more about AI.
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on 9 March 2001
Indeed the best AI presentation I've seen in all my life. Used widely in every university for AI education, with lots of examples, ideas and not cluttered with garbage... Indeed a true AI book!!!
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on 24 August 2008
Be warned, this book is a bit of a door step. Very detailed and generally very good. I would probably recommend some online sites first to get a flavour for the types of algorithms you might need and then selectivly dive into Russel and Norvig to get a more in depth view of the implementation. I feel that this book is not really intedned for cover to cover reading, rather as a resource to allow you to understand the algorithms you implement.

An invaluable tool if you are studying AI at pretty much any level.
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on 12 November 2010
Covers most areas of AI in one book, which I found very useful. Easy to read and easy to understand. The best AI book I've bought in a decade.
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on 20 April 2015
This book (now on it's third edition) is, in my opinion, an absolutely essential book for all computer scientists, and any developer working on algorithms. It is one of my top five computer science books of all time.

The structure, referencing, context and content, are perfectly presented, concise, and understandable. The book also includes exercises for students or lecturers if this is seen as important. Not only does the book cover an introduction to search algorithms efficiently in the 25% of the book, it also provides the best introduction to first order logic I have read.

About 65% of the huge volume covers AI, striking a perfect balance for logical minds, without oversimplifying or avoiding mathematics - as is often found, and without any of the pitfalls found in pure maths texts. (which can sometimes for me feel like they lack either structure or clear concise semantics). Running through the book is an insight into agent-based AI (as and when appropriate for a chapter) building on an introduction to agents in the first part of the book.
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on 15 October 2013
Not for those new to the field and looking for simpler explanation. This book goes into detail, covering most if not all areas in the field.
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on 3 August 2009
I'm a researcher in the domain of ontology engineering. This book is a "must-read" one for every scientist.
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on 6 October 2003
This is not the best place to start learning about AI. The book is poorly written (to the extent that it can become confusing). There is also quite a lot of Maths (OK, you will have to come to terms with this eventually, but it is extremely offputting when one is trying to gain an overview of a topic). Better books to 'start with' are Alison Cawsey's 'Essence of AI' and 'Understanding Intelligence' Pfiefer & Scheier.
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