Artificial Intelligence: A Modern Approach, 3rd Edition

Artificial Intelligence: A Modern Approach, 3rd Edition
PDF
  • eBook:
    Artificial Intelligence: A Modern Approach, 3rd Edition
  • Author:
    Stuart Russell, Peter Norvig
  • Edition:
    3 edition
  • Categories:
  • Data:
    December 11, 2009
  • ISBN:
    0136042597
  • ISBN-13:
    9780136042594
  • Language:
    English
  • Pages:
    1152 pages
  • Format:
    PDF

Book Description
Artificial Intelligence: A Modern Approach, 3e offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence.
Dr. Peter Norvig, contributing Artificial Intelligence author and Professor Sebastian Thrun, a Pearson author are offering a free online course at Stanford University on artificial intelligence. 

According to an article in The New York Times , the course on artificial intelligence is “one of three being offered experimentally by the Stanford computer science department to extend technology knowledge and skills beyond this elite campus to the entire world.” One of the other two courses, an introduction to database software, is being taught by Pearson author Dr. Jennifer Widom.

Content

Part I: Artificial Intelligence
Chapter 1. Introduction
Chapter 2. Intelligent Agents

Part II: Problem-solving
Chapter 3. Solving Problems by Searching
Chapter 4. Beyond Classical Search
Chapter 5. Adversarial Search
Chapter 6. Constraint Satisfaction Problems

Part III: Knowledge, reasoning, and planning
Chapter 7. Logical Agents
Chapter 8. First-Order Logic
Chapter 9. Inference in First-Order Logic
Chapter 10. Classical Planning
Chapter 11. Planning and Acting in the Real World
Chapter 12. Knowledge Representation

Part IV: Uncertain knowledge and reasoning
Chapter 13. Quantifying Uncertainty
Chapter 14. Probabilistic Reasoning
Chapter 15. Probabilistic Reasoning over Time
Chapter 16. Making Simple Decisions
Chapter 17. Making Complex Decisions

Part V: Learning
Chapter 18. Learning from Examples
Chapter 19. Knowledge in Learning
Chapter 20. Learning Probabilistic Models
Chapter 21. Reinforcement Learning

Part VI: Communicating, perceiving, and acting
Chapter 22. Natural Language Processing
Chapter 23. Natural Language for Communication
Chapter 24. Perception
Chapter 25. Robotics

Part VII: Conclusions
Chapter 26. Philosophical Foundations
Chapter 27. AI: The Present and Future

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