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007			cr nn 008mamaa
008			140715s2013 xxu| s |||| 0|eng d
020			_a9781461470526 _9978-1-4614-7052-6
024	7		_a10.1007/978-1-4614-7052-6 _2doi
035			_ato000483840
040			_aSpringer _cSpringer _dRU-ToGU
050		4	_aQ334-342
050		4	_aTJ210.2-211.495
072		7	_aUYQ _2bicssc
072		7	_aTJFM1 _2bicssc
072		7	_aCOM004000 _2bisacsh
082	0	4	_a006.3 _223
100	1		_aSaitta, Lorenza. _eauthor. _9321923
245	1	0	_aAbstraction in Artificial Intelligence and Complex Systems _helectronic resource _cby Lorenza Saitta, Jean-Daniel Zucker.
260			_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2013.
300			_aXVI, 484 p. 202 illus., 95 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
505	0		_aIntroduction -- Abstraction in Different Disciplines -- Abstraction in Artificial Intelligence -- Definitions of Abstraction -- Boundaries of Abstraction -- The KRA Model -- Abstraction Operators and Design Patterns -- Properties of the KRA Model -- Abstraction in Machine Learning -- Simplicity, Complex Systems, and Abstraction -- Case Studies and Applications -- Discussion -- Conclusion.
520			_aAbstraction is a fundamental mechanism underlying both human and artificial perception, representation of knowledge, reasoning and learning. This mechanism plays a crucial role in many disciplines, notably Computer Programming, Natural and Artificial Vision, Complex Systems, Artificial Intelligence and Machine Learning, Art, and Cognitive Sciences. This book first provides the reader with an overview of the notions of abstraction proposed in various disciplines by comparing both commonalities and differences.  After discussing the characterizing properties of abstraction, a formal model, the KRA model, is presented to capture them. This model makes the notion of abstraction easily applicable by means of the introduction of a set of abstraction operators and abstraction patterns, reusable across different domains and applications. It is the impact of abstraction in Artificial Intelligence, Complex Systems and Machine Learning which creates the core of the book.  A general framework, based on the KRA model, is presented, and its pragmatic power is illustrated with three case studies: Model-based diagnosis, Cartographic  Generalization, and learning Hierarchical Hidden Markov Models.
650		0	_aComputer Science. _9155490
650		0	_aData mining. _9306371
650		0	_aArtificial intelligence. _9274099
650		0	_aComputer vision. _9274100
650		0	_aInformation systems. _9303226
650	1	4	_aComputer Science. _9155490
650	2	4	_aArtificial Intelligence (incl. Robotics). _9274102
650	2	4	_aImage Processing and Computer Vision. _9303601
650	2	4	_aData Mining and Knowledge Discovery. _9306372
650	2	4	_aComputer Appl. in Arts and Humanities. _9306361
700	1		_aZucker, Jean-Daniel. _eauthor. _9321924
710	2		_aSpringerLink (Online service) _9143950
773	0		_tSpringer eBooks
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-4614-7052-6
912			_aZDB-2-SCS
999			_c356400