ISBN0137903952

An author of this book is said to have commented that its writing has made him a millionaire. It is used in over 1000 universities for a simple reason, it is good. The book uses the concept of an agent to unify the formerly fragmented field of AI and to link together concepts as diverse as logic programming and ethics. It is very easy to read and touches every area of modern research interest I can think of. The problems have a nice variety of difficulties (although there are no worked-out solutions in the book) and provide a mix between theory and practice, introducing the careful student to concepts and papers not developed in the main text of the chapter. The bibliography is well laid-out and provides useful depth (one of my current research interests was sparked by reading one of the referenced papers in the 2nd chapter).

My only complaint so far (not having finished the entire book) is that some of the definitions in chapter 17's whirlwind introduction to game theory were a little vague. But, a quick look at some other sources clarified things immensely.

It is rare to find a textbook as interesting and clear as this one. If a professor is requiring that you read it, consider yourself fortunate. If you are thinking of reading it yourself, you also are blessed. Look forward to many pleasant evenings.

I am half way through and I like it so far. Frankly I am puzzled by other reviewers complaining about "lack of real code examples", they clearly have not read the book carefully: it comes with tons of sample code (online) written in different languages, publishers/authors simply did not want to waste the precious real estate. The book is nearly a thousand pages already.

Otherwise this is a great CS book. Yes there is some math in it, but don't be scared - there is an appendix with all necessary mathematical background you'll need (and you don't need much). I was surprised to see so much historical references in this book, it teaches you not just about most major branches of AI, but also about how they started and where originated from in a "problem -> solution" form. For instance when they talk about genetic algorithms they actually go ahead and write a comprehensive comparison of analogies between biological evolution, genes and their computer-generated counterparts referencing the original work of Darwin and others.

If you're into AI, applied mathematics or computer science, I have no doubt you'll enjoy this book: it's not too focused on something specific (and something you'd need a PhD to understand) while not too shallow and covers fairly wide spectrum of AI problems, including (!) ethical and philosophical issues like "what happens if we succeed?"

Highly recommended.

Pros: Well organized, Description is clear and complete, good for beginners.
Cons: Examples chosen are not the best, author's attempts at humor are quite lame in most cases.

Form your own opinion on this book, don't let the gushing over this book force you into questioning your instincts

I thought I liked this book at first, but I had confused interest in AI with regard for this book.

Sure this was ground breaking. But, currently, it is bloated, full of wordy, unclear descriptions. I particularly dislike the coverage in: ch. 7, 8, 9 (logics + reasoning). ch. 13, 14 (prob, belief nets). Make the search chapters shorter, fewer. We get the idea, no need to spend so much time on it. Make the logic chapters shorter, dig deeper into those subjects if you want to use that much of the readers time. Scrap chapter 13 or write it over again (refer reader to Pearl's or others coverage of probability). It is partially to elementary, stating obvious rules with very simple usages. The rest of it jumps around, with unclear explanations. Chapter 14, skims past ideas, not enough time spent explaining ideas.

I particularly like the detailed references at the end of each chapter.

After glancing at Winston, Nilsson, and Poole books, I am leaning towards Poole, especially since I am more interested in the knowledge rep and reasoning than other areas.

Following the accolades in the reviews and having a keen interest in AI (as a physician and computer scientist) - I have dived into this book. It took me more than half a year of stubbornly trying to read and understand it. What a disappointment...
On one hand, the math is inaccessible, least you have a major in computer sciences / statistics, math - or all of the above. It seems some, if not all of the math "proofs" are unnecessary for the matter at hand. Unless there are some sinister motives behind these superfluous math complications - such as providing professors with ammunition for students testing. But why should someone interested in AI - get bogged down in this? Is it really what the authors had in mind?
On the other hand there are not enough examples to follow and the examples that are there - are inconsistent and insufficient (for example: the `wumpus' world that is used in the logic chapters, actually succeeds to stir an interest in the reader and then ....it is not followed up in the subsequent chapters such as the one on Bayesian networks)...
Some easy to grasp principles (such as basic propositional logic) are repeated ad nauseam while some difficult subjects (such as MCMC) are left as puzzling axioms, for us to decipher on our own.

I summarize my disappointment asking myself what I got from this effort that I have invested into this book, absorption and digestion wise, professionally speaking:
1. Did this book help me better understand the depth and breadth of the AI domain? - No.
2. Am I able to develop, even conceptually a plan for an AI application / "intelligent agent"? Absolutely not.
3. Did the book clarify for me the fields of logic, machine learning, reasoning, uncertainty, probability and so on? - No. I am as confused now as I was before embarking on this study project, maybe even more so.
4. Am I a smarter person, able to read now the multitude of scientific articles out there on the AI subject - after finishing this book? - No.

The only reason I gave it 2 stars instead of the single one it deserves - is because of the historical and bibliographical summaries the authors have nicely detailed at the end of each chapter. I've seen other books recommended in these reviews - and I intend to look into them shortly. CAVEAT EMPTOR (buyer beware) !