| 000 | 01988nam a22002177a 4500 | ||
|---|---|---|---|
| 999 |
_c696 _d696 |
||
| 005 | 20211113112448.0 | ||
| 008 | 200915b ||||| |||| 00| 0 eng d | ||
| 020 | _a9780070087705 | ||
| 082 |
_a006.3 _bRIC |
||
| 100 |
_aRich, Elaine _91912 |
||
| 245 | _aArtificial intelligence | ||
| 250 | _a3rd | ||
| 260 |
_bMcGraw Hill Education (India) Pvt. Ltd. _aNew Delhi _c2019 |
||
| 300 | _axv, 568 p. | ||
| 365 |
_aINR _b785.00 |
||
| 504 | _aPART 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 | ||
| 520 | _aThis 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. | ||
| 650 |
_aArtificial intelligence _91478 |
||
| 700 |
_aKnight, Kevin _91913 |
||
| 942 |
_2ddc _cBK |
||