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by Elaine Rich,Kevin Knight,Shivashankar B. Nair
Publisher: Tata McGraw-Hill Education Pvt. Ltd.
Price (INR):Rs 785.00
Price (USD): $ 19.62
This book presents both theoretical foundations of AI and an indication of the ways that current techniques can be used in application programs. With the revision, most of the content has been preserved as it is, and an effort has been put in on adding new topics that are in sync with the recent developments in this field.
Table of contents
PART I: PROBLEMS AND SEARCH
Chapter 1. What is Artificial Intelligence?
Chapter 2. Problems, Problem Spaces, and Search
Chapter 3. Heuristic Search Techniques
PART II: KNOWLEDGE REPRESENTATION
Chapter 4. Knowledge Representation Issues
Chapter 5. Using Predicate Logic
Chapter 6. Representing Knowledge Using Rules
Chapter 7. Symbolic Reasoning Under Uncertainty
Chapter 8. Statistical Reasoning
Chapter 9. Weak Slot-and-Filler Structures
Chapter 10. Strong Slot-and-Filler Structures
Chapter 11. Knowledge Representation Summary
PART III ADVANCED TOPICS
Chapter 12. Game Playing
Chapter 13. Planning
Chapter 14. Understanding
Chapter 15. Natural Language Processing
Chapter 16. Parallel and Distributed AI
Chapter 17. Learning
Chapter 18. Connectionist Models
Chapter 19. Common Sense
Chapter 20. Expert Systems 416
Chapter 21. Perception and Action
Chapter 22. Fuzzy Logic Systems
Chapter 23. Genetic Algorithms:Copying Nature's Approaches
Chapter 24. Artificial Immune Systems
Chapter 25. Prolog-The Natural Language of Artificial Intelligence
Chapter 26. Conclusion
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