000			01656nam a22002537a 4500
999			_c360 _d360
003			OSt
005			20180615124002.0
008			160628b xxu||||| |||| 00| 0 eng d
020			_a9780070087705
040			_aDBCETL
041			_aEng.
082			_a001.535 _bRIC
100			_aRich, Elaine
245			_aArtificial intelligence
250			_a3rd ed.
260			_aNew Delhi. : _bTata McGraw-Hill _c2010
300			_axviii, 568 p.; _bPAPER BACK _c23 cm.
500			_aComputer Science
505			_aCONTENTS: Preface to the third edition Preface to the second edition Part I: Problems and search 1. What is artificial intelligence? 2. Problems, problem spaces and search 3. Heuristic search techniques Part II: Knowledge representation 4. Knowledge representation issues 5. Using predicate logic 6. Representing knowledge using rules 7. Symbolic reasoning under uncertainty 8. Statistical reasoning 9. Weak slot-and-filler structures 10. Strong slot-and -filler structures 11. Knowledge representation summary Part III: Advanced topics 12. Game playing 13. Planning 14. Understanding 15. Natural language processing 16. Parallel and distributed AI 17. Learning 18. Connectionist models 19. Common sense 20. Expert systems 21. Perception and action 22. Fuzzy logic systems 23. Genetic algorithms: copying nature's approaches 24. Artificial immune systems 25. Prolog - The natural language of artificial intelligence 26. Conclusion References Author index Subject index
520			_aArtificial, intelligence.
653			_aComputer Science, IT
700			_aKnight, Kevin
700			_aNair, Shivashankar B