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Volumn 47, Issue 5, 2000, Pages 854-882

A neuroidal architecture for cognitive computation

Author keywords

Cognitive computation; Computational learning; Learning relations; Nonmonotonic reasoning; Pac learning; Robust reasoning

Indexed keywords

COGNITIVE COMPUTATION; COMPUTATIONAL LEARNING; LEARNING RELATIONS; NONMONOTONIC REASONING; PAC LEARNING; ROBUST REASONING;

EID: 4243195886     PISSN: 00045411     EISSN: None     Source Type: Journal    
DOI: 10.1145/355483.355486     Document Type: Article
Times cited : (48)

References (39)
  • 1
    • 0004208648 scopus 로고
    • Harvard University Press, Cambridge, Mass. ANGLUIN, D., AND LAIRD, P. 1988. Learning from noisy examples. Mach. Learn. 2, 4
    • ANDERSON, J. R. 1983. The Architecture of Cognition. Harvard University Press, Cambridge, Mass. ANGLUIN, D., AND LAIRD, P. 1988. Learning from noisy examples. Mach. Learn. 2, 4, 343-370.
    • (1983) The Architecture of Cognition. , pp. 343-370
    • Anderson, J.R.1
  • 2
    • 0030387103 scopus 로고    scopus 로고
    • A polynomial time algorithm for learning noisy linear threshold functions
    • IEEE Computer Society Press, Los Alamitos, Calif.
    • BLUM, A., FRIEZE, A., KANNAN, R., AND VEMPALA, S. 1996. A polynomial time algorithm for learning noisy linear threshold functions. In Proceedings of the 37th IEEE Symposium on Theory of Computing. IEEE Computer Society Press, Los Alamitos, Calif., pp. 330-338.
    • (1996) In Proceedings of the 37th IEEE Symposium on Theory of Computing. , pp. 330-338
    • Blum, A.1    Frieze, A.2    Kannan, R.3    Vempala, S.4
  • 3
    • 0027274446 scopus 로고
    • How to use expert advice
    • San Diego, Calif., May 16-18. ACM, New York
    • CESA-BIANCHI, N., FREUND, Y., HAUSSLER, D., SCHAPIRE, R., AND WARMUTH, M. 1993. How to use expert advice. In Proceedings of the 25th Annual ACM Symposium on the Theory of Computing (San Diego, Calif., May 16-18). ACM, New York, pp. 382-392.
    • (1993) Proceedings of the , vol.25 , pp. 382-392
    • Cesa-Bianchi, N.1    Freund, Y.2    Haussler, D.3    Schapire, R.4    Warmuth, M.5
  • 4
    • 0031331853 scopus 로고    scopus 로고
    • Learning noisy perceptrons by a perceptron in polynomial time
    • IEEE Computer Society Press, Los Alamitos, Calif.
    • COHEN, E. 1997. Learning noisy perceptrons by a perceptron in polynomial time. In Proceedings of the 38th IEEE Symposium on Foundation of Computer Science. IEEE Computer Society Press, Los Alamitos, Calif., pp. 514-523.
    • (1997) Proceedings of the 38th IEEE Symposium on Foundation of Computer Science. , pp. 514-523
    • Cohen, E.1
  • 5
    • 0024739191 scopus 로고
    • A general lower bound on the number of examples needed for learning
    • EHRENFEUCHT, A., HAUSSLER, D., KEARNS, M., AND VALIANT, L. 1989. A general lower bound on the number of examples needed for learning. Inf. Coniput. 82, 3, 247-266.
    • (1989) Inf. Coniput. , vol.82 , Issue.3 , pp. 247-266
    • Ehrenfeucht, A.1    Haussler, D.2    Kearns, M.3    Valiant, L.4
  • 7
    • 0032662978 scopus 로고    scopus 로고
    • A Winnow-based approach to context-sensitive spelling correction
    • GOLDING, A. R., AND ROTH, D. 1999. A Winnow-based approach to context-sensitive spelling correction. Mach. Learn. 34, 107-130.
    • (1999) Mach. Learn. , vol.34 , pp. 107-130
    • Golding, A.R.1    Roth, D.2
  • 8
    • 0024082469 scopus 로고
    • Quantifying inductive bias: AI learning algorithms and Valiant's learning framework
    • HAUSSLER, D. 1988. Quantifying inductive bias: AI learning algorithms and Valiant's learning framework. Artif. Int. 36, 177-221.
    • (1988) Artif. Int. , vol.36 , pp. 177-221
    • Haussler, D.1
  • 9
    • 2542455833 scopus 로고
    • Learning conjunctive concepts in structural domains
    • HAUSSLER, D. 1989. Learning conjunctive concepts in structural domains. Mach. Leant. 4, 7-40.
    • (1989) Mach. Leant. , vol.4 , pp. 7-40
    • Haussler, D.1
  • 10
    • 0027188175 scopus 로고
    • Efficient noise-tolerant learning from statistical queries
    • San Diego, Calif., May 16-18. ACM, New York
    • KEARNS, M. 1993. Efficient noise-tolerant learning from statistical queries. In Proceedings of the 25th Annual ACM Symposium on Theory of Computing (San Diego, Calif., May 16-18). ACM, New York, pp. 392-401.
    • (1993) In Proceedings of the 25th Annual ACM Symposium on Theory of Computing , pp. 392-401
    • Kearns, M.1
  • 11
    • 0027640858 scopus 로고
    • Learning in the presence of malicious errors
    • KEARNS, M., AND Li, M. 1993. Learning in the presence of malicious errors. SLAM J. Comput. 22, 4, 807-837.
    • (1993) SLAM J. Comput. , vol.22 , Issue.4 , pp. 807-837
    • Kearns, M.1    Li, M.2
  • 12
    • 0028460231 scopus 로고
    • Efficient distribution-free probabilistic concepts
    • KEARNS, M. J., AND SCHAPIRE, R. E. 1994. Efficient distribution-free probabilistic concepts. J. Comput. Syst. Sci. 48, 3, 464.
    • (1994) J. Comput. Syst. Sci. , vol.48 , Issue.3 , pp. 464
    • Kearns, M.J.1    Schapire, R.E.2
  • 16
    • 34250091945 scopus 로고
    • Learning quickly when irrelevant attributes abound: A new linear-threshold algorithm
    • LITTLESTONE, N. 1988. Learning quickly when irrelevant attributes abound: a new linear-threshold algorithm. Mach. Learn. 2, 285-318.
    • (1988) Mach. Learn. , vol.2 , pp. 285-318
    • Littlestone, N.1
  • 17
    • 85011913774 scopus 로고
    • From on-line to batch learning
    • LITTLESTONE, N. 1989. From on-line to batch learning. In Proceedings of the 2nd Workshop on Computational Learning Theory. Morgan-Kaufmann, San Mateo, Calif., pp. 269-284.
    • (1989) In Proceedings of the , vol.2 , pp. 269-284
    • Littlestone, N.1
  • 18
    • 37349044608 scopus 로고
    • Circumscription-A form of non-raonotonic reasoning
    • MCCARTHY, J. 1980. Circumscription-A form of non-raonotonic reasoning. Artif. Int. 13, 27-39.
    • (1980) Artif. Int. , vol.13 , pp. 27-39
    • Mccarthy, J.1
  • 19
    • 0014638440 scopus 로고
    • Some philosophical problems from the standpoint of artificial intelligence
    • D. Michie, ed. American Elsevier, New York.
    • MCCARTHY, J., AND HAYES, P. J. 1969. Some philosophical problems from the standpoint of artificial intelligence. In Machine Intelligence, vol. 4. D. Michie, ed. American Elsevier, New York.
    • (1969) In Machine Intelligence , vol.4
    • Mccarthy, J.1    Hayes, P.J.2
  • 20
    • 49149141138 scopus 로고
    • Nonmonotonic logic 1
    • McDERMOTT, D., AND DOYLE, J. 1980. Nonmonotonic logic 1. Artif. Int. 13, 1, 41-72.
    • (1980) Artif. Int. , vol.13 , pp. 141-172
    • McDermott, D.1    Doyle, J.2
  • 21
    • 39749093168 scopus 로고
    • The magical number seven, plus or minus two: Some limits on our capacity for processing information
    • MILLER, G. A. 1956. The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psych. Rev. 63, 81-97.
    • (1956) Psych. Rev. , vol.63 , pp. 81-97
    • Miller, G.A.1
  • 25
    • 33749224399 scopus 로고
    • Probabilistic Reasoning in Intelligent Systems: Nettvorks of Plausible Inference
    • PEARL, J. 1988. Probabilistic Reasoning in Intelligent Systems: Nettvorks of Plausible Inference. Morgan-Kaufmann, Los Altos, Calif.
    • (1988) Morgan-Kaufmann, Los Altos, Calif.
    • Pearl, J.1
  • 26
    • 0024092215 scopus 로고
    • Computational limits on learning from examples
    • PITT, L., AND VALIANT, L. G. 1988. Computational limits on learning from examples. J. ACM 35, 965-984.
    • (1988) J. ACM , vol.35 , pp. 965-984
    • Pitt, L.1    Valiant, L.G.2
  • 27
    • 1442267080 scopus 로고
    • Learning decision lists
    • RIVEST, R. L. 1987. Learning decision lists. Mach. Learn. 2, 3, 229-246.
    • (1987) Mach. Learn. , vol.2 , pp. 229-246
    • Rivest, R.L.1
  • 28
    • 0008199690 scopus 로고
    • A formal model of hierarchical concept learning
    • RIVEST, R. L., AND SLOAN, R. 1994. A formal model of hierarchical concept learning. Inf. Comput. 114, 1, 88-114.
    • (1994) Inf. Comput. , vol.114 , Issue.1 , pp. 88-114
    • Rivest, R.L.1    Sloan, R.2
  • 31
    • 0000320045 scopus 로고    scopus 로고
    • A SNOW-based face detector
    • To appear.
    • ROTH, D., YANG, M.-H., AND AHUJA, N. 2000. A SNOW-based face detector. NIPS, To appear.
    • (2000) NIPS
    • Roth, D.1    Yang, M.-H.2    Ahuja, N.3
  • 32
    • 0004294786 scopus 로고
    • Prentice-Hall, Upper Saddle River, N.J. TURING, A. M. 1950. Computing machinery and intelligence. Mind 59, 433-460. (Reprinted in Collected Works of A. M. Turing: Mechanical Intelligence, (D.C. Ince, ed.), North-Holland, 1992).
    • RUSSELL, S., AND NORVIG, P. 1995. Artificial Intelligence. Prentice-Hall, Upper Saddle River, N.J. TURING, A. M. 1950. Computing machinery and intelligence. Mind 59, 433-460. (Reprinted in Collected Works of A. M. Turing: Mechanical Intelligence, (D.C. Ince, ed.), North-Holland, 1992).
    • (1995) Artificial Intelligence.
    • Russell, S.1    Norvig, P.2
  • 34
    • 0021518106 scopus 로고
    • A theory of the learnable
    • VALIANT, L. G. 1984. A theory of the learnable. Commun. ACM 27, 11 (Nov.), 1134-1142.
    • (1984) Commun. ACM , vol.27 , pp. 1134-1142
    • Valiant, L.G.1
  • 37
    • 84949226695 scopus 로고
    • Rationality
    • VALIANT, L. G. 1995. Rationality. In Proceedings of the 8th Annual Conference on Computational Learning Theory (Santa Cruz, Calif., July 5-8). ACM, New York, pp. 3-14.
    • (1995) In Proceedings of the , vol.8 , pp. 5-8
    • Valiant, L.G.1
  • 38
    • 0033225586 scopus 로고    scopus 로고
    • Projection learning
    • VALIANT, L. G. 1999. Projection learning. Mach. Learn. 37, 2, 115-130.
    • (1999) Mach. Learn. , vol.37 , pp. 115-130
    • Valiant, L.G.1
  • 39
    • 0033875407 scopus 로고    scopus 로고
    • Robust logics
    • VALIANT, L. G. 2000. Robust logics. Artif. Int. 117, 231-253.
    • (2000) Artif. Int. , vol.117 , pp. 231-253
    • Valiant, L.G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.