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001 978-1-4614-7052-6
003 DE-He213
005 20200421111657.0
007 cr nn 008mamaa
008 130605s2013 xxu| s |||| 0|eng d
020 _a9781461470526
_9978-1-4614-7052-6
024 7 _a10.1007/978-1-4614-7052-6
_2doi
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.
245 1 0 _aAbstraction in Artificial Intelligence and Complex Systems
_h[electronic resource] /
_cby Lorenza Saitta, Jean-Daniel Zucker.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2013.
300 _aXVI, 484 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
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.
650 0 _aData mining.
650 0 _aArtificial intelligence.
650 0 _aImage processing.
650 0 _aApplication software.
650 1 4 _aComputer Science.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aImage Processing and Computer Vision.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aComputer Appl. in Arts and Humanities.
700 1 _aZucker, Jean-Daniel.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461470519
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-7052-6
912 _aZDB-2-SCS
942 _cEBK
999 _c54782
_d54782