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    Artificial Intelligence: A Modern Approach (Hardback) By (author) Stuart J. Russell, By (author) Peter Norvig


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    DescriptionThis 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.

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  • Full bibliographic data for Artificial Intelligence

    Artificial Intelligence
    A Modern Approach
    Authors and contributors
    By (author) Stuart J. Russell, By (author) Peter Norvig
    Physical properties
    Format: Hardback
    Number of pages: 912
    Width: 198 mm
    Height: 243 mm
    Thickness: 39 mm
    Weight: 1,634 g
    ISBN 13: 9780131038059
    ISBN 10: 0131038052

    BIC E4L: COM
    Nielsen BookScan Product Class 3: S10.3T
    BIC subject category V2: UYQ
    DC20: 006.3
    LC subject heading:
    BISAC V2.8: COM004000, COM044000
    LC classification: Q335.R86 1
    Pearson Education Limited
    Imprint name
    Publication date
    13 December 1994
    Publication City/Country
    Table of contents
    I. ARTIFICIAL INTELLIGENCE. 1. Introduction. 2. Intelligent Agents. II. PROBLEM-SOLVING. 3. Solving Problems by Searching. 4. Informed Search Methods. 5. Game Playing. III. KNOWLEDGE AND REASONING. 6. Agents that Reason Logically. 7. First-order Logic. 8. Building a Knowledge Base. 9. Inference in First-Order Logic. 10. Logical Reasoning Systems. IV. ACTING LOGICALLY. 11. Planning. 12. Practical Planning. 13. Planning and Acting. V. UNCERTAIN KNOWLEDGE AND REASONING. 14. Uncertainty. 15. Probabilistic Reasoning Systems. 16. Making Simple Decisions. 17. Making Complex Decisions. VI. LEARNING. 18. Learning from Observations. 19. Learning with Neural Networks. 20. Reinforcement Learning. 21. Knowledge in Learning. VII. COMMUNICATING, PERCEIVING, AND ACTING. 22. Agents that Communicate. 23. Practical Communication in English. 24. Perception. 25. Robotics. VIII. CONCLUSIONS. 26. Philosophical Foundations. 27. AI: Present and Future.