Using History of Belief States for Adaptive Dialogue Management
Author: 
Xiaobu YuanAuthors Info & Claims
Xiaobu YuanAuthors Info & ClaimsPages 124 - 128
Abstract
This paper applies the theory of information space for an inquiry into dialogue management based upon the partially observable Markov decision process (POMDP) and proposes to maintain the history of belief states for the analysis of trend changes. The establishment of relationship between the number of changing trends in belief states and level of knowledge among users then directs a modification of POMDP-based dialogue manager to assist users achieving their goals by adaptively choosing different sets of policies according to the type of users. Results of experiment demonstrate that this modification allows embodied agents to reduce the length of dialogue while increasing the accuracy of intention discovery.
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Index Terms
- Using History of Belief States for Adaptive Dialogue Management
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Published In
October 2019
135 pages
ISBN:9781450371483
DOI:10.1145/3369318
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In-Cooperation
- UNAM: Universidad Nacional Autonoma de Mexico
- Wuhan Univ.: Wuhan University, China
- NWPU: Northwestern Polytechnical University
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 10 January 2020
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VSIP 2019
VSIP 2019: 2019 International Conference on Video, Signal and Image Processing
October 29 - 31, 2019
Wuhan, China
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