The long-anticipated revision of this best-selling book offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Intelligent Agents. Solving Problems by Searching. Informed Search Methods. Game Playing. Agents that Reason Logically. First-order Logic. Building a Knowledge Base. Inference in First-Order Logic. Logical Reasoning Systems. Practical Planning. Planning and Acting. Uncertainty. Probabilistic Reasoning Systems. Making Simple Decisions. Making Complex Decisions. Learning from Observations. Learning with Neural Networks. Reinforcement Learning. Knowledge in Learning. Agents that Communicate. Practical Communication in English. Perception. Robotics. For those interested in artificial intelligence.
Artificial Intelligence: A Modern Approach introduces basic ideas in artificial intelligence from the perspective of building intelligent agents, which the authors define as "anything that can be viewed as perceiving its environment through sensors and acting upon the environment through effectors." This textbook is up-to-date and is organized using the latest principles of good textbook design. It includes historical notes at the end of every chapter, exercises, margin notes, a bibliography, and a competent index. Artificial Intelligence: A Modern Approach covers a wide array of material, including first-order logic, game playing, knowledge representation, planning, and reinforcement learning.

Customer Rating:
Summary: Who's fault - author or teacher???
Comment: I could not wait to sign up for Artificial Intelligence having worked in the field of Motion Control and being fascinated with robotics and AI from a young age. I cannot express how utterly disappointed I was once the class began and once I opened this book.

It is beyond me why, with as much as we know about human learning patterns and processes in this day and age, that a topic that is so exponentially cool and intriguing could be presented in such a DRY and BORING manner. Perhaps this book is meant for the advanced AI Engineer and not an entry level student? If it is the former then I leave you to the reviews of people far more experienced than I in this field. If it is the latter then this is definitely the wrong book.

Professors, Instructors, Teachers: I implore you to use a different book/approach when introducing your students to Artificial Intelligence. You may attract more interest and sincerity in your students if you do not bore them to tears with material such as this, and/or base your lesson plans off of said type of material.

If you want advanced theory, rules, methods then I'm sure you may find more value in this book. If you want an introduction or beginners/intermediate programming approach to a fascinating field then steer your course far away from this tome.

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Customer Rating:
Summary: Probably the best known book on artificial intelligence
Comment: This is the text that was used in the Artificial Intelligence (AI) computer science course at Wisconsin while I was an undergraduate. It's widely considered one of the best AI references available today. This book was my *sole resource* in implementing decision trees, neural networks, and search and other algoriths such as GSAT, WALKSAT, and Simulated Annealing. It was also very useful for propositional logic programming in PROLOG.

Some reviewers have complained that the text is too long and complicated. To that point I would say that AI is a complex field and to fully understand it you need to go into a good bit of depth. For me personally, it was easier to learn by looking at real-life applications rather than mathematical explanations. Many of my programs were what I would consider to be some of the coolest programs I have ever written -- to me, machine learning is such an incredible concept and the applications are limitless. Futher, there's a TON of information in this text that you can only scratch the surface over the course of a semester. That doesn't make it a bad book....it makes it a great reference.

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Customer Rating:
Summary: Excellent Introductory Text
Comment: I have found this text to be a very readable introduction to the algorithms and methods used in intelligent agents. It assumes the reader has some familiarity with concepts regarding algorithms and implementation but does not assume the reader is an advanced computer scientist. I did not use many of the exercises or online resources but found the text to be excellent.

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Customer Rating:
Summary: Excellent AI book
Comment: Recommended for people looking for a good, but not that mathematical, summary of the field.

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Customer Rating:
Summary: Fantastic Textbook
Comment: As a student with a very strong background in technical fields I am no stranger to heavy studying, reference, and in some cases even total reliance on textbooks. I have encountered many kinds of textbooks, some which get the job done, some which do the same painfully, and unfortunately a select few that were simply inscrutable and probably inhibited my learning more than anything else.

This textbook however, is definitely a cut above all the rest. It's very likely that it's the best textbook I've ever used for any subject, and in my opinion, contains an ideal combination of things:

1. The authors take pains to insert a small "exordium" before every major topic, explaining the topic's history, importance, relevance, and perhaps most uniquely, a text "roadmap" of what the authors are going to explain. The last factor is most refreshing to me, because it helps to concretely focus my attention on the overall organizational structure that the authors have decided to employ, giving each chapter (and the book in general) a much more cohesive and readable feel than is normal for a heavily technical textbook. It also helps to pique my own interest (and therefore extend my attention span) about the overall evolution of AI.

2. Explanations of concepts, whether old, new or concepts too advanced to be discussed at length, are the best I've ever had from a text-based source. I don't find myself re-reading technical explanations very often, and if I do, it's usually only to remember what certain algebraic notations denote in mathematical expressions.

3. The authors have decided to insert a token amount of their own wit and private jokes, whether it's the occasional reference to their own personal experiences in a humorous manner, or a wry quip about a certain topic. I personally find this extremely useful for holding my attention. It makes this textbook seem less like a textbook; in other words, it's much less dry than it could otherwise be. I even think that most of the jokes that the authors make seem quite sincere and genuine, and therefore actually funny, unlike some of the poor attempts I've seen in many others.

4. The examples utilized for explanations are relatively clear and almost instantaneous to absorb, especially when it involves a picture or graphical representation. The one complaint I have about this is that figures are often not on the same page as the text that is describing it. Editing could probably have fixed most occurrences of this situation, but in reality this does not do anything to lessen or tarnish the learning experience. So it's an extremely minor complaint, and has no bearing on the quality of the book.

If it isn't clear by now, this textbook is simply amazing. It's made the learning process much more pleasureable than I imagine it could have been. Currently I am also studying "Introduction to Automata Theory, Languages and Computation" and in comparison, that textbook falls under my last category of "inscrutable". I find myself wanting to tear my hair out and give up on the subject simply because the reading is utterly boring, and the explanations cryptic at best.

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