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Shelves: textbooks , programming , computer-science Holy balls this book has a lot of pages. It starts off strongly for a few hundred pages, but then for no reason at all devotes several chapters to high school-level probability and statistics, before devolving into essentially pointless mathematical show-boating for another few hundred pages.
Then it finishes off with an interesting but not really relevant and highly unrigorous not to mention typo-ridden Holy balls this book has a lot of pages. Chapter 26 Philosophical Foundations , in particular, was a fucking embarrassment, giving more unnecessary to idiots like John Searle and Ray Kurzweil, and wasting paper on absurd hand-wringing over off-the-wall science-fiction scenarios.
AI is too legitimate and interesting a field to justify that sort of crap in a university textbook. I particularly liked that each chapter had an extensive section with historical and biographical notes at the end. 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. 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!
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.
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.
Stuart Jonathan Russell