000			03346nam a2200337 i 4500
999			_c382008 _d382008
001			021156746
003			APU
005			20190114082345.0
008			181216t20172017sz a b 001 0 eng d
010			_a2017943187
020			_a9783319584867 (pbk.)
020			_a3319584863 (pbk.)
035			_a(OCoLC)1022949011
040			_aCCX _beng _cCCX _dWAN
050			_aQ335 _b.E78 2017
100	1		_aErtel, Wolfgang. _941114
245	1	0	_aIntroduction to artificial intelligence / _cWolfgang Ertel ; translated by Nathanael Black ; with illustrations by Florian Mast.
250			_a2nd ed.
260		1	_aCham, Switzerland : _bSpringer, _c2017. _c©2017
300			_axiv, 356 p. : _bill. (some col.) ; _c24 cm.
490	1		_aUndergraduate topics in computer science, _x1863-7310
504			_aIncludes bibliographical references (pages 339-349) and index.
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			_a"This 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;iIncludes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning; 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 Bayestheorem 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."--Back cover.
546			_aTranslated from the German.
650		0	_aArtificial intelligence. _941115
700	1		_aBlack, Nathanael, _etranslator. _941116
700	1		_aMast, Florian, _eillustrator. _941117
830		0	_aUndergraduate topics in computer science. _941118
942			_2lcc _cBook