Gaussian Process based Deep Dyna-Q approach for Dialogue Policy Learning

Guanlin Wu, Wenqi Fang, Ji Wang, Jiang Cao, Weidong Bao, Yang Ping, Xiaomin Zhu, Zheng Wang


Anthology ID:
2021.findings-acl.156
Volume:
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Month:
August
Year:
2021
Address:
Online
Editors:
Chengqing Zong, Fei Xia, Wenjie Li, Roberto Navigli
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1786–1795
Language:
URL:
https://aclanthology.org/2021.findings-acl.156
DOI:
10.18653/v1/2021.findings-acl.156
Bibkey:
Cite (ACL):
Guanlin Wu, Wenqi Fang, Ji Wang, Jiang Cao, Weidong Bao, Yang Ping, Xiaomin Zhu, and Zheng Wang. 2021. Gaussian Process based Deep Dyna-Q approach for Dialogue Policy Learning. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 1786–1795, Online. Association for Computational Linguistics.
Cite (Informal):
Gaussian Process based Deep Dyna-Q approach for Dialogue Policy Learning (Wu et al., Findings 2021)
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PDF:
https://aclanthology.org/2021.findings-acl.156.pdf
Video:
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