5 stars because there is, quite simply, no substitute.

Artificial Intelligence is, in the context of the infant science of computing, a very old and very broad subdiscipline, the "Turing test" having arisen, not only at the same time, but from the same person as many of the foundations of computing itself. Those of us students of a certain age will recall terms like "symbolic" vs. "connectionist" vs. "probabilistic," as well as "scruffies" and "neats." Key figures, events, and schools of thought

Artificial Intelligence is, in the context of the infant science of computing, a very old and very broad subdiscipline, the "Turing test" having arisen, not only at the same time, but from the same person as many of the foundations of computing itself. Those of us students of a certain age will recall terms like "symbolic" vs. "connectionist" vs. "probabilistic," as well as "scruffies" and "neats." Key figures, events, and schools of thought span multiple institutions on multiple continents. In short, a major challenge facing anyone wishing to survey Artificial Intelligence is simply coming up with a unifying theme.

The major accomplishment, in my opinion, of AIMA, then, is that: Russell and Norvig take the hodge-podge of AI research, manage to fit it sensibly into a narrative structure centered on the notion of different kinds of "agents" (not to be confused with that portion of AI research that explicitly refers to its constructs as "agents!") and, having dug the pond and filled it with water, skip a stone across the surface. It's up to the reader whether to follow the arcs of the stone from major subject to major subject, foregoing depth, or whether to pick a particular contact point and concentrate on the eddies propagating from it. For the latter purpose, the extensive bibliography is indispensable.

With all of this said, I have to acknowledge that Russell and Norvig are not entirely impartial AI practitioners. Norvig, in particular, is well-known by now as a staunch Bayesian probabilist who, as Director of Search Quality or Machine Learning or whatever Google has decided to call it today, has made Google the Bayesian powerhouse that it is. (Less known is Norvig's previous stint at high-tech startup Junglee, which was acquired by Amazon. So to some extent Peter Norvig powers both Google and Amazon.) So one can probably claim, not without justification, that AIMA emphasizes Bayesian probability over other approaches.

Finally, as good as AIMA is, it is still a survey. Even with respect to Bayesian probability, the treatment is introductory, as I discovered with some shock upon reading Probability Theory: The Logic of Science. That's OK, though: it's the best introduction I've ever seen.

So read it once for the survey, keep it on your shelf for the bibliography, and refer back to it whenever you find yourself thinking "hey, didn't I read about that somewhere before?"

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Artificial Intelligence: A Modern Approach by Stuart Russell ...