000			03240cam a2200337 i 4500
001			001891
003			MIUC
005			20211111105352.0
008			211111t20182018flua b 000 0 eng
020			_a9780367571641 _q(pbk)
020			_a9781138502383 _q(hbk)
040			_aDLC _beng _cDLC _erda _dDLC _dMIUC
082	0	0	_a006.3 _223
100	1		_aNeapolitan, Richard E. _eauthor _95469
245	1	0	_aArtificial intelligence : _bwith an introduction to machine learning / _cRichard E. Neapolitan, Xia Jiang.
250			_aSecond edition.
264		1	_aBoca Raton : _bCRC Press, Taylor & Francis Group, _c[2018].
264		4	_c©2018
300			_axiii, 466 pages : _billustrations ; _c27 cm.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
490	0		_aChapman & Hall/CRC artificial intelligence and robotics series
500			_a"A Chapman & Hall book."
504			_aIncludes bibliographical references (pages 437-457) and index.
505	0		_a1. Introduction to Artificial Intelligence -- Part 1. Logical Intelligence -- 2. Propositional Logic -- 3. First-Order Logic -- 4. Certain Knowledge Representation -- 5. Learning Deterministic Models -- Part 2. Probabilistic Intelligence -- 6. Probability -- 7. Uncertain Knowledge Representation -- 8. Advanced Properties of Bayesian Network -- 9. Decision Analysis -- 10. Learning Probabilistic Model Parameters -- 11. Learning Probabilistic Model Structure -- 12. Unsupervised Learning and Reinforcement Learning -- Part 3. Emergent Intelligence -- 13. Evolutionary Computation -- 14. Swarm Intelligence -- Part 4: Neural Intelligence -- 15. Neural Networks and Deep Learning -- Part 5. Language Understanding -- 16. Natural Language Understanding.
520			_aThe first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods. The book is divided into five sections that focus on the most useful techniques that have emerged from AI. The first section of the book covers logic-based methods, while the second section focuses on probability-based methods. Emergent intelligence is featured in the third section and explores evolutionary computation and methods based on swarm intelligence. The newest section comes next and provides a detailed overview of neural networks and deep learning. The final section of the book focuses on natural language understanding. Suitable for undergraduate and beginning graduate students, this class-tested textbook provides students and other readers with key AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more.
650		0	_aArtificial intelligence _92114
700	1		_aJiang, Xia, _d1967- _eauthor _95470
942			_2ddc _cBK