Gaussian processes for fast policy optimisation of POMDP-based dialogue managers

Proceedings of the SIGDIAL 2010 Conference: 11th Annual Meeting of the Special Interest Group onDiscourse and Dialogue

Volumn , Issue , 2010, Pages 201-204

  Gasic, M ^a   Jurcicek F ^a   Keizer, S ^a   Mairesse, F ^a   Thomson, B ^a   Yu, K ^a   Young, S ^a  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

DIALOGUE MANAGER; GAUSSIAN PROCESSES; LEARNING PROCESS; OPTIMISATIONS; PARTIALLY OBSERVABLE MARKOV DECISION PROCESS; SPEECH UNDERSTANDING; VOICE MAIL; LEARN+; POLICY LEARNING; POLICY OPTIMIZATION; PROCESS-BASED; UNCERTAINTY;

GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); PERSONAL COMMUNICATION SYSTEMS; REINFORCEMENT LEARNING; UNCERTAINTY ANALYSIS;

OPTIMIZATION; MARKOV PROCESSES;

EID: 84857755225     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

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6. RS Sutton and AG Barto. 1998. Reinforcement Learning: An Introduction. Adaptive Computation and Machine Learning. MIT Press, Cambridge, MA.
7. JD Williams. 2006. Partially Observable Markov Decision Processes for Spoken Dialogue Management. Ph.D. thesis, University of Cambridge.
8. SJ Young, M Gašić, S Keizer, F Mairesse, J Schatzmann, B Thomson, and K Yu. 2010. The Hidden Information State Model: a practical framework for POMDP-based spoken dialogue management. Computer Speech and Language, 24(2):150-174.