000 | 03991nam a2200541 i 4500 | ||
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001 | 6267467 | ||
003 | IEEE | ||
005 | 20220712204714.0 | ||
006 | m o d | ||
007 | cr |n||||||||| | ||
008 | 151228s1994 maua ob 001 eng d | ||
010 | _z 93021600 (print) | ||
020 |
_z9780262560757 _qprint |
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020 |
_a9780262288446 _qelectronic |
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020 |
_z0262560755 _qprint |
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035 | _a(CaBNVSL)mat06267467 | ||
035 | _a(IDAMS)0b000064818b44a7 | ||
040 |
_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL |
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050 | 4 |
_aQ340 _b.C65 1994eb |
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082 | 0 | 0 |
_a006.3 _220 |
245 | 0 | 0 |
_aConstraint-based reasoning / _cedited by Eugene C. Freuder and Alan K. Mackworth. |
264 | 1 |
_aCambridge, Massachusetts : _bMIT Press, _c1994. |
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264 | 2 |
_a[Piscataqay, New Jersey] : _bIEEE Xplore, _c[1994] |
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300 |
_a1 PDF (403 pages) : _billustrations. |
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_atext _2rdacontent |
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337 |
_aelectronic _2isbdmedia |
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_aonline resource _2rdacarrier |
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490 | 1 | _aSpecial issues of <i>artificial intelligence</i> | |
500 | _a"A Bradford book." | ||
500 | _aReprinted from Artificial intelligence, volume 58, numbers 1-3, 1992. | ||
504 | _aIncludes bibliographical references and index. | ||
506 | 1 | _aRestricted to subscribers or individual electronic text purchasers. | |
520 | _aConstraint-based reasoning is an important area of automated reasoning in artificial intelligence, with many applications. These include configuration and design problems, planning and scheduling, temporal and spatial reasoning, defeasible and causal reasoning, machine vision and language understanding, qualitative and diagnostic reasoning, and expert systems. Constraint-Based Reasoning presents current work in the field at several levels: theory, algorithms, languages, applications, and hardware.Constraint-based reasoning has connections to a wide variety of fields, including formal logic, graph theory, relational databases, combinatorial algorithms, operations research, neural networks, truth maintenance, and logic programming. The ideal of describing a problem domain in natural, declarative terms and then letting general deductive mechanisms synthesize individual solutions has to some extent been realized, and even embodied, in programming languages.Contents :- Introduction, E. C. Freuder, A. K. Mackworth.- The Logic of Constraint Satisfaction, A. K. Mackworth.- Partial Constraint Satisfaction, E. C. Freuder, R. J. Wallace.- Constraint Reasoning Based on Interval Arithmetic: The Tolerance Propagation Approach, E. Hyvonen.- Constraint Satisfaction Using Constraint Logic Programming, P. Van Hentenryck, H. Simonis, M. Dincbas.- Minimizing Conflicts: A Heuristic Repair Method for Constraint Satisfaction and Scheduling Problems, S. Minton, M. D. Johnston, A. B. Philips, and P. Laird.- Arc Consistency: Parallelism and Domain Dependence, P. R. Cooper, M. J. Swain.- Structure Identification in Relational Data, R. Dechter, J. Pearl.- Learning to Improve Constraint-Based Scheduling, M. Zweben, E. Davis, B. Daun, E. Drascher, M. Deale, M. Eskey.- Reasoning about Qualitative Temporal Information, P. van Beek.- A Geometric Constraint Engine, G. A. Kramer.- A Theory of Conflict Resolution in Planning, Q. Yang.A Bradford Book. | ||
530 | _aAlso available in print. | ||
538 | _aMode of access: World Wide Web | ||
588 | _aDescription based on PDF viewed 12/28/2015. | ||
650 | 0 |
_aConstraints (Artificial intelligence) _922959 |
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650 | 0 |
_aReasoning. _922773 |
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655 | 0 |
_aElectronic books. _93294 |
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700 | 1 |
_aFreuder, Eugene C. _922960 |
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700 | 1 |
_aMackworth, Alan K. _922961 |
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710 | 2 |
_aIEEE Xplore (Online Service), _edistributor. _922962 |
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710 | 2 |
_aMIT Press, _epublisher. _922963 |
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776 | 0 | 8 |
_iPrint version _z9780262560757 |
830 | 0 |
_aSpecial issues of <i>artificial intelligence</i> _921916 |
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856 | 4 | 2 |
_3Abstract with links to resource _uhttps://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=6267467 |
942 | _cEBK | ||
999 |
_c73121 _d73121 |