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Artificial Intelligence: A Modern Approach (2nd Edition)
Books: Computers: Artificial Intelligence: Item 7
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Artificial Intelligence: A Modern Approach (2nd Edition)by Stuart J. Russell and Peter Norvig
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61 of 76 people found the following review helpful: The optimal learning algorithm for learning A.I., September 23, 2001 Reviewer:Lee Carlson (Saint Louis, Missouri USA) - Progress in the field of artificial intelligence has executed a random walk after establishing itself with a bang in the 1950s. Optimistic predictions of the future of A.I. in that decade only partially came true in the decades after that. Currently, the field is divided up into subfields going by the names data mining, computational intelligence, intelligent agent theory, expert systems, etc. This book is the best book available for learning about this fascinating and important subject. The applications of A.I. are enormous, and will increase dramatically in the decades ahead. Indeed the prospects are very exciting, and the authors themselves have been involved heavily in extending the frontiers of the subject. Some of the main points of the book that really stand out include: 1. The useful exercises at the end of each chapter. 2. The discussion of simple reflex and goal-based agents. 3. The treatment of constraint satisfaction problems and heuristics for these kinds of problems. 4. The overview of iterative improvement algorithms, particularly the discussion of simulated annealing. 5. The discussion of propositional logic and its limitations as an effective A.I. paradigm. 6. The treatment of first-order logic and its use in modeling simple reflex agents, change, and its use in situation calculus. There is a good overview of inference in first-order logic in chapter 9 of the book, including completeness and resolution. 7. The treatment of logic programming systems; the Prolog language is discussed as a logical programming language. Noting that Prolog cannot specify constraints on values, the authors discuss constraint logic programming (CLP) as an alternative logic programming language that allows constraints. 8. The discussion of semantic networks and description logics. 9. The treatment of conditional programming via the conditional partial-order planner (CPOP). 10. Representing knowledge in an uncertain domain and the semantics and inference in belief networks. 11. The brief discussions on stochastic simulation methods and fuzzy logic. 12. The discussion on computational learning theory 13. The treatment of neural networks, especially the discussion of multilayer feed-forward networks and the comparison between belief networks and neural networks. 14. The brief discussion on genetic algorithms and evolutionary programming. 15. The discussion on explanation-based learning and the technique of memoization. 16. The (excellent) overview of inductive logic programming. This relatively recent area was new to me at the time of reading so I appreciated the discussion. The authors briefly mention the approach of discovery systems and the Automated Mathematician (AM). 17. The interesting discussion of telepathic communication between robots via the exchange of internal representations. 18. The discussion on a formal grammar for a subset of English and the extensive treatment of natural language processing. 19. The discussion of speech recognition and the use of hidden Markov models and the Viterbi algorithm. 20. The fascinating discussion on robotics, particularly the treatment of configuration spaces, which brings in some techniques from computational geometry and topology. 21. The discussion on the philosophical ramifications of A.I. Future developments in A.I. will provide a unique testing ground for philosophy, in a way that will be unparalleled in the history of philosophy. Philosophers critical of A.I. will have the opportunity to check whether their arguments against the possibility of "strong A.I.", are in fact true.
Product Review
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. --This text refers to an out of print or unavailable edition of this title.
Product Review
"The publication of this textbook was a major step forward, not only for the teaching of AI, but for the unified view of the field that this book introduces. Even for experts in the field, there are important insights in almost every chapter." — Prof. Thomas Dietterich, Oregon State
"Just terrific. The book I've always been waiting forthe AI bible for the next decade." — Prof. Gerd Brewka (Vienna)
"A marvelous achievement, a truly beautiful book!" — Prof. Selmer Bringsjord, RPI
"It's a great book, with incredible breadth and depth, and very well-written. Everyone I know who has used it in their class has loved it." — Prof. Haym Hirsh, Rutgers
"I am deeply impressed by its unprecedented quality in presenting a coherent, balanced, broad and deep, enjoyable picture of the field of AI. It will become tire standard text for the years to come." — Prof. Wolfgang Bibel, Darmstadt
"Terrific! Well-written and well-organised, with comprehensive coverage of the material that every AI student should know." — Prof. Martha Pollack (Michigan)
"Outstanding Its descriptions are extremely clear and readable; its organization is excellent; its examples are motivating; and its coverage is scholarly and throughout! will deservedly dominate the field for some time." — Prof. Nils Nilsson, Stanford
"The best book available nowIt's almost as good as the book Charniak and I wrote, but more up to date. (Okay I'll admit it, it may even be better than our book.)" — Prof. Drew McDermott, Yale
"A magisterial wide scope account of the entire field of Artificial Intelligence that will enlighten professors as well as students." — Dr. Alan Kay
"This is the book that made me love AI." — Student (Indonesia)
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