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Volumn , Issue , 2008, Pages 568-575

Knows what it knows: A framework for self-aware learning

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING SYSTEMS; REINFORCEMENT; ROBOT LEARNING;

EID: 56449122733     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (87)

References (21)
  • 2
    • 1942450194 scopus 로고    scopus 로고
    • Technical Report CMU-RI-TR-01-25, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA
    • Bagnell, J., Ng, A. Y., & Schneider, J. (2001). Solving uncertain Markov decision problems (Technical Report CMU-RI-TR-01-25). Robotics Institute, Carnegie Mellon University, Pittsburgh, PA.
    • (2001) Solving uncertain Markov decision problems
    • Bagnell, J.1    Ng, A.Y.2    Schneider, J.3
  • 3
    • 0028517062 scopus 로고
    • Separating distribution-free and mistake-bound learning models over the Boolean domain
    • Blum, A. (1994). Separating distribution-free and mistake-bound learning models over the Boolean domain. SIAM Journal on Computing, 23, 990-1000.
    • (1994) SIAM Journal on Computing , vol.23 , pp. 990-1000
    • Blum, A.1
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    • 0041965975 scopus 로고    scopus 로고
    • R-MAX - a general polynomial time algorithm for near-optimal reinforcement learning
    • Brafman, R. I., & Tennenholtz, M. (2002). R-MAX - a general polynomial time algorithm for near-optimal reinforcement learning. Journal of Machine Learning Research, 3, 213-231.
    • (2002) Journal of Machine Learning Research , vol.3 , pp. 213-231
    • Brafman, R.I.1    Tennenholtz, M.2
  • 7
    • 0028424239 scopus 로고
    • Improving generalization with active learning
    • Cohn, D. A., Atlas, L., & Ladner, R. E. (1994). Improving generalization with active learning. Machine Learning, 15, 201-221.
    • (1994) Machine Learning , vol.15 , pp. 201-221
    • Cohn, D.A.1    Atlas, L.2    Ladner, R.E.3
  • 12
    • 23244466805 scopus 로고    scopus 로고
    • Doctoral dissertation, Gatsby Computational Neuroscience Unit, University College London
    • Kakade, S. M. (2003). On the sample complexity of reinforcement learning. Doctoral dissertation, Gatsby Computational Neuroscience Unit, University College London.
    • (2003) On the sample complexity of reinforcement learning
    • Kakade, S.M.1
  • 14
    • 0036832954 scopus 로고    scopus 로고
    • Near-optimal reinforcement learning in polynomial time
    • Kearns, M. J., & Singh, S. P. (2002). Near-optimal reinforcement learning in polynomial time. Machine Learning, 49, 209-232.
    • (2002) Machine Learning , vol.49 , pp. 209-232
    • Kearns, M.J.1    Singh, S.P.2
  • 15
    • 0037400054 scopus 로고    scopus 로고
    • An empirical study of two approaches to sequence learning for anomaly detection
    • Lane, T., & Brodley, C. E. (2003). An empirical study of two approaches to sequence learning for anomaly detection. Machine Learning, 51, 73-107.
    • (2003) Machine Learning , vol.51 , pp. 73-107
    • Lane, T.1    Brodley, C.E.2
  • 16
    • 34250091945 scopus 로고
    • Learning quickly when irrelevant attributes abound: A new linear-threshold algorithm
    • Littlestone, N. (1987). Learning quickly when irrelevant attributes abound: A new linear-threshold algorithm. Machine Learning, 2, 285-318.
    • (1987) Machine Learning , vol.2 , pp. 285-318
    • Littlestone, N.1
  • 20
    • 0021518106 scopus 로고
    • A theory of the learnable
    • Valiant, L. G. (1984). A theory of the learnable. Communications of the ACM, 27, 1134-1142.
    • (1984) Communications of the ACM , vol.27 , pp. 1134-1142
    • Valiant, L.G.1
  • 21
    • 49549125826 scopus 로고    scopus 로고
    • Maximizing classifier utility when training data is costly
    • Weiss, G. M., & Tian, Y. (2006). Maximizing classifier utility when training data is costly. SIGKDD Explorations, 8, 31-38.
    • (2006) SIGKDD Explorations , vol.8 , pp. 31-38
    • Weiss, G.M.1    Tian, Y.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.