Artificial Intelligence : a Modern Approach

By: Contributor(s): Material type: TextTextPublication details: Nueva Jersey : Pearson Education, 2010Edition: 3rd edDescription: xviii, 1132 p. : ilISBN:
  • 9780136042594
Subject(s):
Contents:
I. Artificial intelligence -- 1. Introduction -- 2. Intelligent Agents -- II. problem-solving -- 3. Solving Problem by Searching -- 4. Beyond Classical Search -- 5. Adversarial Search -- 5. Constraint Satisfaction Problems -- III. Knowledge, reasoning, and planning -- 7. Logical Agents -- 8. First-Order Logic -- 9. Inference in First-Order Logic -- 10. Classical Planning -- 11. Planning and Acting in the Real World -- 12. Knowledge Representation -- IV. Uncertain knowledge and reasoning -- 13. Quantifying Uncertainly -- 14. Probabilistic Reasoning -- 15. Probabilistic reasoning over Time -- 16. Making Simple decisions -- 17. Making Complex Decisions -- V. Learning -- 18. Learning from Examples -- 19. Knowledge in Learning -- 20. Learning Probabilistic Models -- 21. Reinforcement Learning -- VI. Communicating, perceiving, and acting -- 22. Natural Language Processing -- 23. Natural Language for Communication -- 24. Perception -- 25. Robotics -- VII. Conclusions -- 26. Philosophical Foundations -- 27. AI: The Present and Future
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Item type Current library Call number Status Date due Barcode
Libros Libros Biblioteca Fac.Informática I.2 RUS (Browse shelf(Opens below)) Available DIF-04257

I. Artificial intelligence -- 1. Introduction -- 2. Intelligent Agents -- II. problem-solving -- 3. Solving Problem by Searching -- 4. Beyond Classical Search -- 5. Adversarial Search -- 5. Constraint Satisfaction Problems -- III. Knowledge, reasoning, and planning -- 7. Logical Agents -- 8. First-Order Logic -- 9. Inference in First-Order Logic -- 10. Classical Planning -- 11. Planning and Acting in the Real World -- 12. Knowledge Representation -- IV. Uncertain knowledge and reasoning -- 13. Quantifying Uncertainly -- 14. Probabilistic Reasoning -- 15. Probabilistic reasoning over Time -- 16. Making Simple decisions -- 17. Making Complex Decisions -- V. Learning -- 18. Learning from Examples -- 19. Knowledge in Learning -- 20. Learning Probabilistic Models -- 21. Reinforcement Learning -- VI. Communicating, perceiving, and acting -- 22. Natural Language Processing -- 23. Natural Language for Communication -- 24. Perception -- 25. Robotics -- VII. Conclusions -- 26. Philosophical Foundations -- 27. AI: The Present and Future

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