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View chapters 3 and 4 from the upcoming Third Edition. For one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Click on "Features" tab below for more information Resources: Visit the author's website http://aima.cs.berkeley.edu/ to access both student and instructor resources including Power Point slides, syllabus. homework and exams, and solutions text problems.
| ISBN | 0130803022 | | Pages | 1132 | | ISBN13 | 9780130803023
(What's this?) | | Weight (grammes) | 1896 | | Publisher | Pearson Education (US) | | Published in | Upper Saddle River | | Imprint | Pearson Education (US) | | Previous ISBN | 9780133601244 | | Format | Paperback | | Height (mm) | 254 | | Publication date | 13 Jan 2003 | | Width (mm) | 203 | | DEWEY | 006.3 | | Academic level | Professional / Scholarly | | DEWEY edition | DC21 | | Alternative ISBN | 9780137903955 |
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I. ARTIFICIAL INTELLIGENCE. 1. Introduction. 2. Intelligent Agents. II. PROBLEM-SOLVING. 3. Solving Problems by Searching. 4. Informed Search and Exploration. 5. Constraint Satisfaction Problems. 6. Adversarial Search. III. KNOWLEDGE AND REASONING. 7. Logical Agents. 8. First-Order Logic. 9. Inference in First-Order Logic. 10. Knowledge Representation. IV. PLANNING. 11. Planning. 12. Planning and Acting in the Read World. V. UNCERTAIN KNOWLEDGE AND REASONING. 13. Uncertainty. 14. Probabilistic Reasoning Systems. 15. Probabilistic Reasoning Over Time. 16. Making Simple Decisions. 17. Making Complex Decisions. VI. LEARNING. 18. Learning from Observations. 19. Knowledge in Learning. 20. Statistical Learning Methods. 21. Reinforcement Learning. VII. COMMUNICATING, PERCEIVING, AND ACTING. 22. Agents that Communicate. 23. Text Processing in the Large. 24. Perception. 25. Robotics. VIII. CONCLUSIONS. 26. Philosophical Foundations. 27. AI: Present and Future.
"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)  Be the first to write a customer review
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