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020 _a9780857292995
_9978-0-85729-299-5
040 _cMX-MeUAM
050 4 _aQ334-342
050 4 _aTJ210.2-211.495
082 0 4 _a006.3
_223
100 1 _aErtel, Wolfgang.
_eauthor.
245 1 0 _aIntroduction to Artificial Intelligence
_h[recurso electrónico] /
_cby Wolfgang Ertel.
264 1 _aLondon :
_bSpringer London,
_c2011.
300 _aXII, 316 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
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 _aThe ultimate aim of artificial intelligence (A.I.) is to understand intelligence and to build intelligent software and robots that come close to the performance of humans. On their way towards this goal, A.I. researchers have developed a number of quite different subdisciplines. This concise and accessible Introduction to Artificial Intelligence supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. The textbook presents concrete algorithms and applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks and reinforcement learning. Topics and features: Presents an application-focused and hands-on approach to learning the subject Provides study exercises of varying degrees of difficulty at the end of each chapter, with solutions given at the end of the book Supports the text with 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 learning Contains an extensive bibliography for deeper reading on further topics Supplies additional teaching resources, including lecture slides and training data for learning algorithms, at the website http://www.hs-weingarten.de/~ertel/aibook Students of computer science and other technical natural sciences will find this easy-to-read textbook excellent for self-study, a high-school level of knowledge of mathematics being the only prerequisite to understanding the material. With its extensive tools and bibliography, it is an ideal, quick resource on A.I. Dr. Wolfgang Ertel is a professor at the Collaborative Center for Applied Research on Service Robotics at the Ravensburg-Weingarten University of Applied Sciences, Germany.
650 0 _aComputer science.
650 0 _aArtificial intelligence.
650 1 4 _aComputer Science.
650 2 4 _aArtificial Intelligence (incl. Robotics).
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780857292988
830 0 _aUndergraduate Topics in Computer Science,
_x1863-7310
856 4 0 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-0-85729-299-5
596 _a19
942 _cLIBRO_ELEC
999 _c198422
_d198422