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Volumn , Issue , 2006, Pages 273-278

Speeding up model-based diagnosis by a heuristic approach to solving sat

Author keywords

Diagnosis; Machine learning; Model based reasoning; Qualitative reasoning; SAT problem

Indexed keywords

CASE BASED REASONING; COMPUTER SIMULATION; LEARNING SYSTEMS; MAXIMUM LIKELIHOOD; MODEL CHECKING;

EID: 38049101382     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (5)

References (20)
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    • Technical Report IAI-TR-93-3, Department of Computer Science, University of Bonn, March 1, Tue, 10 Oct 98 00:00:00 GMT
    • Hermann Stamm-Wilbrandt. Programming in propositional logic or reductions: Back to the roots (satisfiability). Technical Report IAI-TR-93-3, Department of Computer Science, University of Bonn, March 1 1993. Tue, 10 Oct 98 00:00:00 GMT.
    • (1993)
    • Stamm-Wilbrandt, H.1
  • 9
    • 20144365208 scopus 로고    scopus 로고
    • The TPTP problem library - v2.1.0
    • Technical Report JCU-CS-97/8, Department of Computer Science, James Cook University, 15 December
    • Christian B. Suttner and Geoff Sutcliffe. The TPTP problem library - v2.1.0. Technical Report JCU-CS-97/8, Department of Computer Science, James Cook University, 15 December 1997.
    • (1997)
    • Suttner, C.B.1    Sutcliffe, G.2
  • 10
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    • Test pattern generation for realistic bridge faults in CMOS ICs
    • Altoona, Pa, USA, October, IEEE Computer Society Press
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    • Ferguson, F.1    Larrabee, T.2
  • 11
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    • ModGen: Theorem proving by model generation
    • Menlo Park, CA, USA, July 31-August 4, AAAI Press
    • Sun Kim and Hantao Zhang. ModGen: Theorem proving by model generation. In Proceedings of the 12th National Conference on Artificial Intelligence. Volume 1, pages 162-167, Menlo Park, CA, USA, July 31-August 4 1994. AAAI Press.
    • (1994) Proceedings of the 12th National Conference on Artificial Intelligence , vol.1 , pp. 162-167
    • Kim, S.1    Zhang, H.2
  • 12
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    • An efficient propositional prover
    • William McCune, editor, Proceedings of the 14th International Conference on Automated deduction, of, Berlin, July 13-17, Springer
    • Hantao Zhang. SATO: An efficient propositional prover. In William McCune, editor, Proceedings of the 14th International Conference on Automated deduction, volume 1249 of LNAI, pages 272-275, Berlin, July 13-17 1997. Springer.
    • (1997) LNAI , vol.1249 , pp. 272-275
    • Hantao Zhang, S.A.T.O.1
  • 19
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  • 20
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    • Irrelevant Features and the Subset Selection Problem
    • William W. Cohen and Haym Hirsh, editors, San Francisco, CA, Morgan Kaufmann
    • George H. John, Ron Kohavi, and Karl Pfleger. Irrelevant Features and the Subset Selection Problem. In William W. Cohen and Haym Hirsh, editors, Machine Learning: Proceedings of the Eleventh International Conference, pages 121-129, San Francisco, CA, 1994. Morgan Kaufmann.
    • (1994) Machine Learning: Proceedings of the Eleventh International Conference , pp. 121-129
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.