Artificial intelligence a modern approach
In this third edition, the authors have updated the treatment of all major areas. A new organizing principle--the representational dimension of atomic, factored, and structured models--has been added. Significant new material has been provided in areas such as partially observable search, contingenc...
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| Format: | Book |
| Language: | English |
| Published: |
Upper Saddle River, N.J.
Pearson
2010
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| Edition: | 3rd ed. |
| Series: | Prentice Hall series in artificial intelligence.
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| 020 | |a 9780132071482 (pbk.) | ||
| 020 | |a 0132071487 (pbk.) | ||
| 020 | |a 9780136042594 (hbk.) | ||
| 020 | |a 0136042597 (hbk.) | ||
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| 040 | |a UPNM | ||
| 090 | |a Q 335 |b .R86 2010 | ||
| 100 | |a Russell, Stuart J. | ||
| 245 | 1 | 0 | |a Artificial intelligence |b a modern approach |c Stuart J. Russell and Peter Norvig ; contributing writers, Ernest Davis ... [et al.]. |
| 250 | |a 3rd ed. | ||
| 260 | |a Upper Saddle River, N.J. |b Pearson |c 2010 | ||
| 300 | |a xviii, 1132 p. |b ill. |c 26 cm. | ||
| 490 | 1 | |a Prentice Hall series in artificial intelligence | |
| 500 | |a " International edition" -- cover. | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | 0 | |a Machine generated contents note: |g I. |t Artificial Intelligence -- |g 1. |t Introduction -- |g 2. |t Intelligent Agents -- |g II. |t Problem-solving -- |g 3. |t Solving Problems by Searching -- |g 4. |t Beyond Classical Search -- |g 5. |t Adversarial Search -- |g 6. |t Constraint Satisfaction Problems -- |g III. |t Knowledge, reasoning, and planning -- |g 7. |t Logical Agents -- |g 8. |t First-Order Logic -- |g 9. |t Inference in First-Order Logic -- |g 10. |t Classical Planning -- |g 11. |t Planning and Acting in the Real World -- |g 12. |t Knowledge Representation -- |g IV. |t Uncertain knowledge and reasoning -- g 13. |t Quantifying Uncertainty -- |g 14. |t Probabilistic Reasoning -- |g 15. |t Probabilistic Reasoning over Time -- |g 16. |t Making Simple Decisions -- |g 17. |t Making Complex Decisions -- |g V. |t Learning -- |g 18. |t Learning from Examples -- |g 19. |t Knowledge in Learning -- |g 20. |t Learning Probabilistic Models -- |g 21. |t Reinforcement Learning -- |g VI. |t Communicating, perceiving, and acting -- |g 22. |t Natural Language Processing -- |g 23. |t Natural Language for Communication -- |g 24. |t Perception -- |g 25. |t Robotics -- |g VII. |t Conclusions -- |g 26. |t Philosophical Foundations -- |g 27. |t AI: The Present and Future -- |g A. |t Mathematical background -- |g B. |t Notes on Languages and Algorithms. |
| 520 | |a In this third edition, the authors have updated the treatment of all major areas. A new organizing principle--the representational dimension of atomic, factored, and structured models--has been added. Significant new material has been provided in areas such as partially observable search, contingency planning, hierarchical planning, relational and first-order probability models, regularization and loss functions in machine learning, kernel methods, Web search engines, information extraction, and learning in vision and robotics. The book also includes hundreds of new exercises. | ||
| 592 | |a 00033034 |b 03/06/2013 |c RM457.71 |h YPiJ Books | ||
| 650 | 0 | |a Artificial intelligence. | |
| 700 | 1 | |a Norvig, Peter. | |
| 830 | 0 | |a Prentice Hall series in artificial intelligence. | |
| 999 | |a vtls000048566 |c 48014 |d 48014 | ||