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Volumn 11, Issue 1, 1999, Pages 59-77

Connectionist inductive learning and logic programming system

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; FEEDFORWARD NEURAL NETWORKS; KNOWLEDGE ACQUISITION; LOGIC PROGRAMMING;

EID: 0033164970     PISSN: 0924669X     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1008328630915     Document Type: Article
Times cited : (173)

References (60)
  • 6
    • 0344506699 scopus 로고    scopus 로고
    • Neural networks and structured knowledge
    • edited by Ch. Herrmann, F. Reine, and A. Strohmaier, Logos-Verlag: Berlin
    • F.J. Kurfess, "Neural networks and structured knowledge," in Knowledge Representation in Neural Networks, edited by Ch. Herrmann, F. Reine, and A. Strohmaier, Logos-Verlag: Berlin, pp. 5-22, 1997.
    • (1997) Knowledge Representation in Neural Networks , pp. 5-22
    • Kurfess, F.J.1
  • 7
    • 0344506698 scopus 로고
    • Energy minimization and the satisfiability of propositional calculus
    • G. Pinkas, "Energy minimization and the satisfiability of propositional calculus," Neural Computation, vol. 3, no. 2, 1991.
    • (1991) Neural Computation , vol.3 , Issue.2
    • Pinkas, G.1
  • 8
    • 0029368629 scopus 로고
    • Reasoning, nonmonotonicity and learning in connectionist networks that capture propositional knowledge
    • G. Pinkas, "Reasoning, nonmonotonicity and learning in connectionist networks that capture propositional knowledge," Artificial Intelligence, vol. 77, pp. 203-247, 1995.
    • (1995) Artificial Intelligence , vol.77 , pp. 203-247
    • Pinkas, G.1
  • 13
    • 0001609012 scopus 로고
    • Reasoning about termination of pure prolog programs
    • K.R. Apt and D. Pedreschi, "Reasoning about termination of pure prolog programs," Information and Computation, vol. 106, pp. 109-157, 1993.
    • (1993) Information and Computation , vol.106 , pp. 109-157
    • Apt, K.R.1    Pedreschi, D.2
  • 14
    • 0028550693 scopus 로고
    • Metric methods-three examples and a theorem
    • M. Fitting, "Metric methods-three examples and a theorem," Journal of Logic Programming, vol. 21, pp. 113-127, 1994.
    • (1994) Journal of Logic Programming , vol.21 , pp. 113-127
    • Fitting, M.1
  • 16
    • 0028529307 scopus 로고
    • Knowledge-based artificial neu ral networks
    • G.G. Towell and J.W. Shavlik, "Knowledge-based artificial neu" ral networks," Artificial Intelligence, vol. 70, no. 1, pp. 119-165, 1994.
    • (1994) Artificial Intelligence , vol.70 , Issue.1 , pp. 119-165
    • Towell, G.G.1    Shavlik, J.W.2
  • 17
    • 0000646059 scopus 로고
    • Learning internal representations by error propagation
    • edited by D.E. Rumelhart and J.L. McClelland, MIT Press
    • D.E. Rumelhart, G.E. Hinton, and R.J. Williams, "Learning internal representations by error propagation," in Parallel Distributed Processing, edited by D.E. Rumelhart and J.L. McClelland, MIT Press, vol. 1, pp. 318-363, 1986.
    • (1986) Parallel Distributed Processing , vol.1 , pp. 318-363
    • Rumelhart, D.E.1    Hinton, G.E.2    Williams, R.J.3
  • 18
    • 0028429573 scopus 로고
    • Inductive logic programming: Theory and methods
    • S. Muggleton and L. Raedt, "Inductive logic programming: Theory and methods," Journal of Logic Programming, vol. 19, pp. 629-679, 1994.
    • (1994) Journal of Logic Programming , vol.19 , pp. 629-679
    • Muggleton, S.1    Raedt, L.2
  • 22
    • 0000331883 scopus 로고
    • Introduction to the theory of neural computation
    • Santa Fe Institute, Addison-Wesley Publishing Company
    • J. Hertz, A. Krogh, and R.G. Palmer, "Introduction to the theory of neural computation," Studies in the Science of Complexity, Santa Fe Institute, Addison-Wesley Publishing Company, 1991.
    • (1991) Studies in the Science of Complexity
    • Hertz, J.1    Krogh, A.2    Palmer, R.G.3
  • 23
    • 0028425519 scopus 로고
    • Logic programming and negation: A survey
    • K.R. Apt and N. Bol, "Logic programming and negation: A survey," Journal of Logic Programming, vol. 19, pp.9-71, 1994.
    • (1994) Journal of Logic Programming , vol.19 , pp. 9-71
    • Apt, K.R.1    Bol, N.2
  • 24
    • 0002065879 scopus 로고
    • Parallel algorithms for shared-memory machines
    • edited by J. van Leeuwen, Elsevier Science
    • R.M. Karp and V Ramachandran, "Parallel algorithms for shared-memory machines," in Handbook of Theoretical Computer Science, edited by J. van Leeuwen, Elsevier Science, vol. 17, pp. 869-941, 1990.
    • (1990) Handbook of Theoretical Computer Science , vol.17 , pp. 869-941
    • Karp, R.M.1    Ramachandran, V.2
  • 25
    • 0024880831 scopus 로고
    • Multilayer feedforward networks are universal approximators
    • K. Hornik, M. Stinchcombe, and H. White, "Multilayer feedforward networks are universal approximators," Neural Networks, vol. 2, pp. 359-366, 1989.
    • (1989) Neural Networks , vol.2 , pp. 359-366
    • Hornik, K.1    Stinchcombe, M.2    White, H.3
  • 26
    • 0030585103 scopus 로고    scopus 로고
    • Analog versus discrete neural networks
    • B. DasGupta and G. Schinitger, "Analog versus discrete neural networks," Neural Computation, vol. 8, pp. 805-818, 1996.
    • (1996) Neural Computation , vol.8 , pp. 805-818
    • DasGupta, B.1    Schinitger, G.2
  • 28
    • 0042799215 scopus 로고
    • Inserting and extracting knowledge from constrained error backpropagation networks
    • Sydney
    • R. Andrews and S. Geva, "Inserting and extracting knowledge from constrained error backpropagation networks," in Proc. Sixth Australian Conference on Neural Networks, Sydney, 1995.
    • (1995) Proc. Sixth Australian Conference on Neural Networks
    • Andrews, R.1    Geva, S.2
  • 32
    • 0027678679 scopus 로고
    • The extraction of refined rules from knowledge based neural networks
    • G.G. Towell and J.W. Shavlik, "The extraction of refined rules from knowledge based neural networks," Machine Learning, vol. 13, no. 1, pp. 71-101, 1993.
    • (1993) Machine Learning , vol.13 , Issue.1 , pp. 71-101
    • Towell, G.G.1    Shavlik, J.W.2
  • 33
    • 0030631792 scopus 로고    scopus 로고
    • Extracting rules from neural networks by pruning and hidden-unit splitting
    • R. Setiono, "Extracting rules from neural networks by pruning and hidden-unit splitting," Neural Computation, vol. 9, pp. 205-225, 1997.
    • (1997) Neural Computation , vol.9 , pp. 205-225
    • Setiono, R.1
  • 34
    • 0029484103 scopus 로고
    • A survey and critique of techniques for extracting rules from trained artificial neural networks
    • R. Andrews, J. Diederich, and A.B. Tickle, "A survey and critique of techniques for extracting rules from trained artificial neural networks," Knowledge-based Systems, vol. 8, no. 6, pp. 1-37, 1995.
    • (1995) Knowledge-based Systems , vol.8 , Issue.6 , pp. 1-37
    • Andrews, R.1    Diederich, J.2    Tickle, A.B.3
  • 38
    • 33744584654 scopus 로고
    • Induction of decision trees
    • J.R. Quinlan, "Induction of decision trees," Machine Learning, vol. 1, pp. 81-106, 1986.
    • (1986) Machine Learning , vol.1 , pp. 81-106
    • Quinlan, J.R.1
  • 39
    • 0343442766 scopus 로고
    • Knowledge acquisition via incremental conceptual clustering
    • D.H. Fisher, "Knowledge acquisition via incremental conceptual clustering," Machine Learning, vol. 2, pp. 139-172, 1987.
    • (1987) Machine Learning , vol.2 , pp. 139-172
    • Fisher, D.H.1
  • 40
    • 0025342573 scopus 로고
    • Consensus patterns in DNA
    • Academic Press: Orlando
    • G.D. Stormo, "Consensus patterns in DNA," Methods in Enzymology, Academic Press: Orlando, vol. 183, pp. 211-221, 1990.
    • (1990) Methods in Enzymology , vol.183 , pp. 211-221
    • Stormo, G.D.1
  • 41
    • 0028407918 scopus 로고
    • Theory refinement combining analytical and empirical methods
    • D. Ourston and R.J. Mooney, "Theory refinement combining analytical and empirical methods," Artificial Intelligence, vol. 66, pp. 273-310, 1994.
    • (1994) Artificial Intelligence , vol.66 , pp. 273-310
    • Ourston, D.1    Mooney, R.J.2
  • 43
    • 8844261754 scopus 로고
    • The utility of knowledge in inductive learning
    • M. Pazzani and D. Kibler, "The utility of knowledge in inductive learning," Machine Learning, vol. 9, pp. 57-94, 1992.
    • (1992) Machine Learning , vol.9 , pp. 57-94
    • Pazzani, M.1    Kibler, D.2
  • 44
    • 0344937102 scopus 로고
    • Using symbolic learning to improve knowledge-based neural networks
    • G.G. Towell and J.W. Shavlik, "Using symbolic learning to improve knowledge-based neural networks," in Proc. AAAI'94, 1994.
    • (1994) Proc. AAAI'94
    • Towell, G.G.1    Shavlik, J.W.2
  • 45
    • 77951505493 scopus 로고
    • Classical negation in logic programs and disjunctive databases
    • Springer-Verlag
    • M. Gelfond and V. Lifschitz, "Classical negation in logic programs and disjunctive databases," New Generation Computing, Springer-Verlag, vol. 9, pp. 365-385, 1991.
    • (1991) New Generation Computing , vol.9 , pp. 365-385
    • Gelfond, M.1    Lifschitz, V.2
  • 46
    • 49149147322 scopus 로고
    • A logic for default reasoning
    • R. Reiter, "A logic for default reasoning," Artificial Intelligence, vol. 13, pp. 81-132, 1980.
    • (1980) Artificial Intelligence , vol.13 , pp. 81-132
    • Reiter, R.1
  • 48
    • 0344506241 scopus 로고
    • A prioritized contextual default logic: Curing anomalous extensions with a simple abnormality default theory
    • Springer-Verlag: Saarbrucken, Germany, LNAI 861
    • G. Zaverucha, "A prioritized contextual default logic: Curing anomalous extensions with a simple abnormality default theory," in Proc. KI'94, Springer-Verlag: Saarbrucken, Germany, LNAI 861, pp. 260-271, 1994.
    • (1994) Proc. KI'94 , pp. 260-271
    • Zaverucha, G.1
  • 54
    • 0024511781 scopus 로고
    • Escherichia coli promoters: Consensus as it relates to spacing class, specificity, repeat substructure, and three dimensional organization
    • M.C. O'Neill, "Escherichia coli promoters: Consensus as it relates to spacing class, specificity, repeat substructure, and three dimensional organization," Journal of Biological Chemistry, vol. 264, pp. 5522-5530, 1989.
    • (1989) Journal of Biological Chemistry , vol.264 , pp. 5522-5530
    • O'Neill, M.C.1
  • 55
    • 85158010005 scopus 로고
    • Refinement of approximately correct domain theories by knowledge-based neural networks
    • Boston
    • G.G. Towell, J.W. Shavlik, and M.O. Noordewier, "Refinement of approximately correct domain theories by knowledge-based neural networks," in Proc. AAAI'90, Boston, pp. 861-866, 1990.
    • (1990) Proc. AAAI'90 , pp. 861-866
    • Towell, G.G.1    Shavlik, J.W.2    Noordewier, M.O.3
  • 57
    • 0007523219 scopus 로고
    • Integration of neural heuristics into knowledge-based inference
    • L.M. Fu, "Integration of neural heuristics into knowledge-based inference," Connection Science, vol. 1, pp. 325-340, 1989.
    • (1989) Connection Science , vol.1 , pp. 325-340
    • Fu, L.M.1
  • 59
    • 0026170884 scopus 로고
    • Logical versus analogical, symbolic versus connectionist, neat versus scruffy
    • M. Minsky, "Logical versus analogical, symbolic versus connectionist, neat versus scruffy," AI Magazine, vol. 12, no. 2, 1991.
    • (1991) AI Magazine , vol.12 , Issue.2
    • Minsky, M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.