000			03708nam a22003737a 4500
999			_c31637 _d31637
001			21735670
003			PACU
005			20240306082254.0
006			m |o d |
007			cr |||||||||||
008			180119s2017 gw |||| o |||| 0|eng
010			_a 2019753363
020			_a9783319584867 _cAvailable
035			_a(DE-He213)978-3-319-58487-4
040			_aDLC _beng _erda _cPACU _dPACU
050			_aQ335 _b.E75513 2017
100	1		_aErtel, Wolfgang, _eauthor.
245	1	0	_aIntroduction to Artificial Intelligence / _cby Wolfgang Ertel.
250			_a2nd ed.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _cc.2017.
300			_axvi, 356 pages : _billustrations ; _c24cm
490	1		_aUndergraduate Topics in Computer Science, _x1863-7310
505	0		_aIntroduction -- Propositional Logic -- First-order Predicate Logic -- Limitations of Logic -- Logic Programming with PROLOG -- Search, Games and Problem Solving -- Reasoning with Uncertainty -- Machine Learning and Data Mining -- Neural Networks -- Reinforcement Learning -- Solutions for the Exercises.
520			_aThis accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning. Fully revised and updated, this much-anticipated second edition also includes new material on deep learning. Topics and features: Presents an application-focused and hands-on approach to learning, with supplementary teaching resources provided at an associated website Contains numerous study exercises and solutions, highlighted examples, definitions, theorems, and illustrative cartoons Includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learn ing Reports on developments in deep learning, including applications of neural networks to generate creative content such as text, music and art (NEW) Examines performance evaluation of clustering algorithms, and presents two practical examples explaining Bayes' theorem and its relevance in everyday life (NEW) Discusses search algorithms, analyzing the cycle check, explaining route planning for car navigation systems, and introducing Monte Carlo Tree Search (NEW) Includes a section in the introduction on AI and society, discussing the implications of AI on topics such as employment and transportation (NEW) Ideal for foundation courses or modules on AI, this easy-to-read textbook offers an excellent overview of the field for students of computer science and other technical disciplines, requiring no more than a high-school level of knowledge of mathematics to understand the material. Dr. Wolfgang Ertel is a professor at the Institute for Artificial Intelligence at the Ravensburg-Weingarten University of Applied Sciences, Germany.
588			_aDescription based on publisher-supplied MARC data.
650		0	_aArtificial intelligence.
650	1	4	_aArtificial Intelligence. _0https://scigraph.springernature.com/ontologies/product-market-codes/I21000
776	0	8	_iPrint version: _tIntroduction to artificial intelligence. _z9783319584867 _w(DLC) 2017943187
776	0	8	_iPrinted edition: _z9783319584867
776	0	8	_iPrinted edition: _z9783319584881
830		0	_aUndergraduate Topics in Computer Science, _x1863-7310
906			_a0 _bibc _corigres _du _encip _f20 _gy-gencatlg
942			_2lcc _cBK _kQ335 _m.E75513 2017