Artificial Intelligence: A Modern Approach (3rd Edition),   ISBN:9780136042594

Customer Rating: 

Sadly the third eddition feels like part of the textbook racket where new editions are created with more of an aim at increasing profits than increasing quality. Besides that gripe I found the book to be a better than average textbook. I've used it much more heaviled that many other textbooks I've purchased.

Customer Rating: 

- With AIMA 1st Edition, I had relearned AI anew from a fresh, insightful and wonderfully pedagogical perspective.
Best computer science textbook ever.
- With AIMA 2nd Edition, I got a lot of recent advances in AI brought to me in the same way, even if presented at times in a way that was too concise for a textbook, and read more like an encyclopedia.
Yet, great 2nd Edition.

- This 3rd Edition is alas AIMA 2.1 and not the AIMA 3.0 that I was waiting for. The new material and new insightful way to organize past material are both scant. Certainly not worth the price for those who own the 2nd Edition.

Don't get me wrong, if you are about to buy your first AI textbook, this is a great buy as it is still light years ahead of the competition. But some chapters that were getting really thin and outdated in 2009 did not get significant updating.

This is particularly true for knowledge representation. Missing are all the recent yet already consolidated advances brought about by the new solutions to the frame problem (such as the fluent calculus), default reasoning, abduction-based and case-based diagnosis, rule-based reasoning (such as constraint handling rules, answer sets, object-oriented logic programming etc.), in short, all forms of reasoning that are neither pure deduction, nor probabilistic. Advances on multi-agent reasoning are also not covered. I understand that to summarize AI in 1000 pages many important topics will not make the cut, but I feel, as a researcher on the topic for the past 25 years and lecturer on it for the past 15 years, that this 3rd edition contains obsolete stuff from the 80s (like frames, semantic networks, production systems, situation calculus, etc.) instead of their modern substitute listed above.

In short, after two Herculean efforts, it seems like the authors put far less work in this one. As a result, we are left without an truly comprehensive and up-to-date text to teach AI and agents. I hope the incoming text by David Poole will cover some of the weaknesses of this AIMA 2.1.

Customer Rating: 

Artificial Intelligence: A Modern approach is a very good book which explores concepts in the area of AI. It covers most of the techniques in the area (there are some important AI techniques missing such as KDD and Data Mining), however it doesn't go deep in any concept so if you're looking for a specialized reference this is not the one.

The third edition of this book offers a few changes:
- a very updated list of references
- some (not many) new exercises
- they rewrote concepts in order to be up-to-date with the state of the art
- they changed the order of some chapters

All in all, it is still a very good introductory book, it is well-written and very easy to understand. If you are new in the field this is the first textbook to read.

Customer Rating: 

Artificial Intelligence is one of the most interesting fields in Computer Engineering and Science. Yet this book takes the subject and turns it into a guide to search algorithms. Every chapter in this book is like a different book about either different algorithms, different game puzzles to solve, or statistics. All sections of the book may teach you about their relative subject but it has no big picture view into the field of Artificial Intelligence. The textbook has in it, pseudo-code (fake code) so that any programmer of any language can learn, yet the pseudo-code does just the opposite, it's so badly written that no programmer of any language who hasn't already seen the algorithm would be able to recreate it.

This textbook is long and repetitive. It covers many algorithms and for this reason I give it one star, otherwise it wouldn't be worth reading. If you're trying to learn AI, you will hate this book, because it floods you with all sorts of useless information for specific situations that you may never face.

AI isn't about solving puzzles or the various algorithms we use; if you're creating specific algorithms for your AI then you are not truly creating AI, you're creating a simple program.

Artificial Intelligence is the field that attempts to simulate the human brain or to create an intelligence that rivals the human brain. The human brain isn't about the various algorithms. In fact, a true AI would have to be able to generate it's own algorithms for each problem, not use existing ones. This is the old way of thinking of AI, that we can just hard-code everything into AI.

If we teach everyone just the various algorithms we will never improve the field of AI.

Customer Rating: 

I've only had the book for about a week and given that it's finals week I have not been able to devote as much time to reading it as I would like. With that said I find myself constantly reaching for it because it is both well written, though a little verbose at times, and compelling. It seems the authors have considered every little detail, even the cover is intricate and completely relevant to the topic. Assuming the rest of the book is as good as the first part I expect this book to be a reference for a long time to come.