"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 for...the 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 now...It'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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This is an introduction to the theory and practice of artificial intelligence. It uses an intelligent agent as the unifying theme throughout, and covers areas that are sometimes underemphasized elsewhere. These include reasoning under uncertainty, learning, natural language, vision and robotics. The book also explains in detail some of the more recent ideas in the field, including simulated annealing, memory-bounded search, global ontologies, dynamic belief networks, neural nets, inductive logic programming, computational learning theory, and reinforcement learning. An instructor's manual with transparency masters is also available.