000			03378cam a22003974a 4500
001			u4410
003			SA-PMU
005			20210418122932.0
008			071207s2009 maua b 001 0 eng
010			_a 2007050376
040			_aDLC _beng _cDLC _dBAKER _dYDXCP _dC#P _dBTCTA _dU9S _dALAUL _dW2U _dUXS _dDEBBG _dOCLCQ
020			_a9780321545893 (alk. paper)
020			_a0321545893 (alk. paper)
020			_a9780132090018 (pbk.)
020			_a0132090015 (pbk.)
035			_a(OCoLC)183611012
050	0	0	_aQ335 _b.L84 2009
082	0	0	_a006.3 _222
100	1		_aLuger, George F.
245	1	0	_aArtificial intelligence : _bstructures and strategies for complex problem solving / _cGeorge F. Luger.
250			_a6th ed.
260			_aBoston : _bPearson Addison-Wesley, _cc2009.
300			_axxiii, 754 p. : _bill. ; _c24 cm.
504			_aIncludes bibliographical references (p. 705-733) and indexes.
520			_aIn this accessible, comprehensive text, George Luger captures the essence of artificial intelligence-solving the complex problems that arise wherever computer technology is applied. Key representation techniques including logic, semantic and connectionist networks, graphical models, and many more are introduced. Presentation of agent technology and the use of ontologies are added. A new machine-learning chapter is based on stochastic methods, including first-order Bayesian networks, variants of hidden Markov models, inference with Markov random fields and loopy belief propagation. A new presentation of parameter fitting with expectation maximization learning and structure learning using Markov chain Monte Carlo sampling. Use of Markov decision processes in reinforcement learning. Natural language processing with dynamic programming (the Earley parser) and other probabilistic parsing techniques including Viterbi, are added. A new supplemental programming book is available online and in print: "AI Algorithms in Prolog, Lisp and Java (TM). "References and citations are updated throughout the Sixth Edition. For all readers interested in artificial intelligence.
505	0		_apt. I. Artificial intelligence : its roots and scope -- 1. AI : history and applications -- pt. II. Artificial intelligence as representation and search -- 2. The predicate calculus -- 3. Structures and strategies for state space search -- 4. Heuristic search -- 5. Stochastic methods -- 6. Control and implementation of state space search -- pt. III. Capturing intelligence : the AI challenge -- 7. Knowledge representation -- 8. Strong method problem solving -- 9. Reasoning in uncertain situations -- pt. IV. Machine iearning -- 10. Machine learning : symbol-based -- 11. Machine learning : connectionist -- 12. Machine learning : genetic and emergent -- 13. Machine learning : probabilistic -- pt. V. Advanced topics for AI problem solving -- 14. Automated reasoning -- 15. Understanding natural language -- pt. VI. Epilogue -- 16. Artificial intelligence as empirical enquiry.
650		0	_aArtificial intelligence.
650		0	_aKnowledge representation (Information theory)
650		0	_aProblem solving.
650		0	_aProlog (Computer program language)
650		0	_aLISP (Computer program language)
856	4	1	_3Table of contents _uhttp://catdir.loc.gov/catdir/toc/fy0803/2007050376.html
942			_cBOOK
994			_aZ0 _bSUPMU
596			_a1 2
999			_c684 _d684