000			04653nam a2200565 i 4500
001			8618068
003			IEEE
005			20220712204931.0
006			m o d
007			cr |n|||||||||
008			190319s2018 mau ob 001 eng d
020			_a9780262349802 _qelectronic bk.
020			_z0262349809 _qelectronic bk.
020			_z9780262038942
020			_z0262038943
035			_a(CaBNVSL)mat08618068
035			_a(IDAMS)0b00006488a42c52
040			_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL
050		4	_aBF311
082	0	4	_a153 _223
100	1		_aForbus, Kenneth D., _eauthor. _925527
245	1	0	_aQualitative representations : _bhow people reason and learn about the continuous world / _cKenneth D. Forbus.
264		1	_aCambridge : _bThe MIT Press, _c[2018]
264		2	_a[Piscataqay, New Jersey] : _bIEEE Xplore, _c[2019]
300			_a1 PDF (xvi, 424 pages).
336			_atext _2rdacontent
337			_aelectronic _2isbdmedia
338			_aonline resource _2rdacarrier
490	1		_aMIT Press
504			_aIncludes bibliographical references and index.
505	0		_aIntroduction and preliminaries -- Introduction -- Representation -- Reasoning -- Analogy -- Dynamics -- Quantity -- Relationships between quantities -- Qualitative process theory -- Examples using QP theory -- Causality -- Qualitative simulation and reasoning about change -- Modeling -- Analogy in dynamics -- Dynamics in language -- Space -- Qualitative spatial reasoning: a theoretical framework -- Qualitative spatial calculi -- Understanding sketches and diagrams -- Learning and reasoning -- Learning and conceptual change -- Commonsense reasoning -- Expert reasoning -- Summary and new directions -- Summary -- New directions -- Bibliography -- Notes -- Index.
506			_aRestricted to subscribers or individual electronic text purchasers.
520			_aAn argument that qualitative representations -- symbolic representations that carve continuous phenomena into meaningful units -- are central to human cognition. In this book, Kenneth Forbus proposes that qualitative representations hold the key to one of the deepest mysteries of cognitive science: how we reason and learn about the continuous phenomena surrounding us. Forbus argues that qualitative representations -- symbolic representations that carve continuous phenomena into meaningful units -- are central to human cognition. Qualitative representations provide a basis for commonsense reasoning, because they enable practical reasoning with very little data; this makes qualitative representations a useful component of natural language semantics. Qualitative representations also provide a foundation for expert reasoning in science and engineering by making explicit the broad categories of things that might happen and enabling causal models that help guide the application of more quantitative knowledge as needed. Qualitative representations are important for creating more human-like artificial intelligence systems with capabilities for spatial reasoning, vision, question answering, and understanding natural language. Forbus discusses, among other topics, basic ideas of knowledge representation and reasoning; qualitative process theory; qualitative simulation and reasoning about change; compositional modeling; qualitative spatial reasoning; and learning and conceptual change. His argument is notable both for presenting an approach to qualitative reasoning in which analogical reasoning and learning play crucial roles and for marshaling a wide variety of evidence, including the performance of AI systems. Cognitive scientists will find Forbus's account of qualitative representations illuminating; AI scientists will value Forbus's new approach to qualitative representations and the overview he offers.
530			_aAlso available in print.
538			_aMode of access: World Wide Web
588	0		_aPrint version record.
650		0	_aCognition. _923500
650		0	_aReasoning. _922773
650		0	_aSpace perception. _920819
650		7	_aCognition. _2fast _923500
650		7	_aReasoning. _2fast _922773
650		7	_aSpace perception. _2fast _920819
655		4	_aElectronic books. _93294
710	2		_aIEEE Xplore (Online Service), _edistributor. _925528
710	2		_aMIT Press, _epublisher. _925529
776	0	8	_iPrint version: _aForbus, Kenneth D. _tQualitative representations. _dCambridge, MA : MIT Press, [2018] _z9780262038942 _w(DLC) 2018010193 _w(OCoLC)1029789097
830		0	_aMIT Press _925529
856	4	2	_3Abstract with links to resource _uhttps://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=8618068
942			_cEBK
999			_c73576 _d73576