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Volumn , Issue , 2009, Pages 2475-2478

Reinforcement learning for dialog management using least-squares policy iteration and fast feature selection

Author keywords

Dialog management; Partially observable Markov decision processes; Spoken dialog systems

Indexed keywords

DIALOG MANAGEMENT; DIALOG SYSTEMS; FEATURE SELECTION; LEAST SQUARE; PARTIALLY OBSERVABLE MARKOV DECISION PROCESS; POLICY ITERATION; SPOKEN DIALOG SYSTEMS;

EID: 70450186275     PISSN: None     EISSN: 19909772     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (37)

References (15)
  • 1
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    • (2000) IEEE Trans. Speech Audio Process , vol.8 , Issue.1 , pp. 11-23
    • Levin, E.1    Pieraccini, R.2    Eckert, W.3
  • 2
    • 84880707672 scopus 로고    scopus 로고
    • Spoken dialogue management using probabilistic reasoning
    • N. Roy, J. Pineau, and S. Thrun, "Spoken dialogue management using probabilistic reasoning," in ACL, 2000, pp. 93-100.
    • (2000) ACL , pp. 93-100
    • Roy, N.1    Pineau, J.2    Thrun, S.3
  • 3
    • 51449120317 scopus 로고    scopus 로고
    • Hybrid reinforcement/ supervised learning of dialogue policies from fixed data sets
    • J. Henderson, O. Lemon, and K. Georgila, "Hybrid reinforcement/ supervised learning of dialogue policies from fixed data sets," Computational Linguistics, vol. 34, no. 4, pp. 487-511, 2008.
    • (2008) Computational Linguistics , vol.34 , Issue.4 , pp. 487-511
    • Henderson, J.1    Lemon, O.2    Georgila, K.3
  • 4
    • 51449096257 scopus 로고    scopus 로고
    • Bayesian update of dialogue state for robust dialogue systems
    • B. Thomson, J. Schatzmann, and S. Young, "Bayesian update of dialogue state for robust dialogue systems," in ICASSP, 2008.
    • (2008) ICASSP
    • Thomson, B.1    Schatzmann, J.2    Young, S.3
  • 5
  • 7
    • 35748957806 scopus 로고    scopus 로고
    • Proto-value functions: A Laplacian framework for learning representation and control in Markov decision processes
    • S. Mahadevan and M. Maggioni, "Proto-value functions: A Laplacian framework for learning representation and control in Markov decision processes," Journall of Machine Learning Research, vol. 8, pp. 2169-2231, 2007.
    • (2007) Journall of Machine Learning Research , vol.8 , pp. 2169-2231
    • Mahadevan, S.1    Maggioni, M.2
  • 10
    • 33847202724 scopus 로고
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    • R. S. Sutton, "Learning to predict by the methods of temporal differences," Machine Learning, vol. 3, pp. 9-44, 1988.
    • (1988) Machine Learning , vol.3 , pp. 9-44
    • Sutton, R.S.1
  • 11
    • 70450138370 scopus 로고    scopus 로고
    • J. D. Williams, Demonstration of a POMDP voice dialer, In ACL/HLT, 2008.
    • J. D. Williams, "Demonstration of a POMDP voice dialer," In ACL/HLT, 2008.
  • 12
    • 70450127475 scopus 로고    scopus 로고
    • The best of both worlds: Unifying conventional dialog systems and pomdps
    • -, "The best of both worlds: Unifying conventional dialog systems and pomdps," in ICSLP-08, 2008.
    • (2008) ICSLP-08
  • 13
    • 14344279109 scopus 로고    scopus 로고
    • An application of reinforcement learning to dialogue strategy selection in a spoken dialogue system for email
    • M. Walker, "An application of reinforcement learning to dialogue strategy selection in a spoken dialogue system for email," Journal of Articial Intelligence Research, vol. 12, pp. 387-416, 2000.
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  • 14
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    • Automatic learning and evaluation of user-centered objective functions for dialogue system optimisation
    • V. Rieser and O. Lemon, "Automatic learning and evaluation of user-centered objective functions for dialogue system optimisation," in Proc LREC, Marrakech, 2008.
    • (2008) Proc LREC, Marrakech
    • Rieser, V.1    Lemon, O.2
  • 15
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    • Using dialogue acts to learn better repair strategies for spoken dialogue systems
    • Las Vegas
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    • Frampton, M.1    Lemon, O.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.