Skip to main content

Application on Healthcare Dialog Management

  • Chapter
  • First Online:
Book cover Building Dialogue POMDPs from Expert Dialogues

Part of the book series: SpringerBriefs in Electrical and Computer Engineering ((BRIEFSSPEECHTECH))

  • 483 Accesses

Abstract

In this chapter, we show the application of our proposed methods on healthcare dialog management (Chinaei et al. 2014).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Chinaei, H. R., Chaib-Draa, B., & Chaib, B. (2014). Dialogue strategy learning in healthcare: A systematic approach for learning dialogue models from data. In Proceedings of the 5th Workshop on Speech and Language Processing for Assistive Technologies (SLPAT’14), Association for Computational Linguistics (ACL), Baltimore, MD.

    Google Scholar 

  • Choi, J., & Kim, K.-E. (2011). Inverse reinforcement learning in partially observable environments. Journal of Machine Learning Research, 12, 691–730.

    MATH  Google Scholar 

  • Cuayáhuitl, H., van Otterlo, M., Dethlefs, N., & Frommberger, L. (2013). Machine learning for interactive systems and robots: A brief introduction. In Proceedings of the 2nd Workshop on Machine Learning for Interactive Systems: Bridging the Gap Between Perception, Action and Communication (pp. 19–28). New York: ACM.

    Google Scholar 

  • Ji, S., Parr, R., Li, H., Liao, X., & Carin, L. (2007). Point-based policy iteration. In Proceedings of the 22nd National Conference on Artificial Intelligence - Volume 2 (AAAI’07), Vancouver, BC.

    Google Scholar 

  • Ng, A. Y., & Russell, S. J. (2000). Algorithms for inverse reinforcement learning. In Proceedings of the 17th International Conference on Machine Learning (ICML’00), Stanford, CA.

    Google Scholar 

  • Pineau, J., West, R., Atrash, A., Villemure, J., & Routhier, F. (2011). On the feasibility of using a standardized test for evaluating a speech-controlled smart wheelchair. International Journal of Intelligent Control and Systems, 16(2), 124–131.

    Google Scholar 

  • Png, S., & Pineau, J. (2011). Bayesian reinforcement learning for POMDP-based dialogue systems. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP’11), Prague.

    Google Scholar 

  • Spaan, M., & Vlassis, N. (2005). Perseus: Randomized point-based value iteration for POMDPs. Journal of Artificial Intelligence Research, 24(1), 195–220.

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2016 The Authors

About this chapter

Cite this chapter

Chinaei, H., Chaib-draa, B. (2016). Application on Healthcare Dialog Management. In: Building Dialogue POMDPs from Expert Dialogues. SpringerBriefs in Electrical and Computer Engineering(). Springer, Cham. https://doi.org/10.1007/978-3-319-26200-0_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-26200-0_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26198-0

  • Online ISBN: 978-3-319-26200-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics