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Dialog policy decides what and how a task-oriented dialog system will respond, and plays a vital role in delivering effective conversations.
Paradise: A framework for evaluating spoken dialogue agents
Marilyn A Walker, Diane J Litman, Candace A Kamm, and Alicia Abella. 1997 · 1997
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Spoken dialogue management using probabilistic reasoning
Nicholas Roy, Joelle Pineau, and Sebastian Thrun. 2000 · 2000
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Dialogue act modeling for automatic tagging and recognition of conversational speech
Andreas Stolcke, Klaus Ries, Noah Coccaro, Elizabeth Shriberg, Rebecca Bates, Daniel Jurafsky, Paul Taylor, Rachel Martin, Carol Van Ess-Dykema, and Marie Meteer. 2000 · 2000
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Agenda-based user simulation for bootstrapping a pomdp dialogue system
Jost Schatzmann, Blaise Thomson, Karl Weilhammer, Hui Ye, and Steve Young. 2007 · 2007
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Maximum entropy inverse reinforcement learning
Brian D Ziebart, Andrew Maas, J Andrew Bagnell, and Anind K Dey. 2008 · 2008
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Learning the reward model of dialogue pomdps from data
Abdeslam Boularias, Hamid R Chinaei, and Brahim Chaib-draa. 2010 · 2010
Earlier work this paper cites.
Modeling interaction via the principle of maximum causal entropy
Brian D Ziebart, J Andrew Bagnell, and Anind K Dey. 2010 · 2010
Earlier work this paper cites.
Bayesian inverse reinforcement learning for modeling conversational agents in a virtual environment
Lina M Rojas Barahona and Christophe Cerisara. 2014 · 2014
Earlier work this paper cites.
Temporal supervised learning for inferring a dialog policy from example conversations
Lihong Li, He He, and Jason D Williams. 2014 · 2014
Earlier work this paper cites.
Policy learning for domain selection in an extensible multi-domain spoken dialogue system
Zhuoran Wang, Hongliang Chen, Guanchun Wang, Hao Tian, Hua Wu, and Haifeng Wang. 2014 · 2014
Earlier work this paper cites.
Policy committee for adaptation in multi-domain spoken dialogue systems
Milica Gašić, Nikola Mrkšić, Pei-Hao Su, David Vandyke, Tsung-Hsien Wen, and Steve Young. 2015 · 2015
Earlier work this paper cites.
Deep reinforcement learning for multi-domain dialogue systems
Heriberto Cuayáhuitl, Seunghak Yu, Ashley Williamson, and Jacob Carse. 2016 · 2016
Earlier work this paper cites.
Policy networks with two-stage training for dialogue systems
Mehdi Fatemi, Layla El Asri, Hannes Schulz, Jing He, and Kaheer Suleman. 2016 · 2016
Earlier work this paper cites.
A connection between generative adversarial networks, inverse reinforcement learning, and energy-based models
Chelsea Finn, Paul Christiano, Pieter Abbeel, and Sergey Levine. 2016 · 2016
Cited alongside, same era.
Generative adversarial imitation learning
Jonathan Ho and Stefano Ermon. 2016 · 2016
Cited alongside, same era.
On-line active reward learning for policy optimisation in spoken dialogue systems
Pei-Hao Su, Milica Gašić, Nikola Mrkšić, Lina M Rojas Barahona, Stefan Ultes, David Vandyke, Tsung-Hsien Wen, and Steve Young. 2016 · 2016
Cited alongside, same era.
The dialog state tracking challenge series: A review
Jason D Williams, Antoine Raux, and Matthew Henderson. 2016 · 2016
Cited alongside, same era.
Towards end-to-end learning for dialog state tracking and management using deep reinforcement learning
Tiancheng Zhao and Maxine Eskenazi. 2016 · 2016
Cited alongside, same era.
Wasserstein generative adversarial networks
Feudal reinforcement learning for dialogue management in large domains
Iñigo Casanueva, Paweł Budzianowski, Pei-Hao Su, Stefan Ultes, Lina M Rojas Barahona, Bo-Hsiang Tseng, and Milica Gašić. 2018 · 2018
Later among the works it cites.
Learning robust rewards with adversarial inverse reinforcement learning
Justin Fu, Katie Luo, and Sergey Levine. 2018 · 2018
Later among the works it cites.
User modeling for task oriented dialogues
Izzeddin Gür, Dilek Hakkani-Tür, Gokhan Tür, and Pararth Shah. 2018 · 2018
Later among the works it cites.
Decoupling strategy and generation in negotiation dialogues
He He, Derek Chen, Anusha Balakrishnan, and Percy Liang. 2018 · 2018
Later among the works it cites.
Sequicity: Simplifying task-oriented dialogue systems with single sequence-to-sequence architectures
Wenqiang Lei, Xisen Jin, Min-Yen Kan, Zhaochun Ren, Xiangnan He, and Dawei Yin. 2018 · 2018
Later among the works it cites.
Adversarial learning of task-oriented neural dialog models
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Martin Arjovsky, Soumith Chintala, and Léon Bottou. 2017 · 2017
Cited alongside, same era.
Agent-aware dropout dqn for safe and efficient on-line dialogue policy learning
Lu Chen, Xiang Zhou, Cheng Chang, Runzhe Yang, and Kai Yu. 2017 · 2017
Cited alongside, same era.
Towards end-to-end reinforcement learning of dialogue agents for information access
Bhuwan Dhingra, Lihong Li, Xiujun Li, Jianfeng Gao, Yun-Nung Chen, Faisal Ahmed, and Li Deng. 2017 · 2017
Cited alongside, same era.
Composite task-completion dialogue policy learning via hierarchical deep reinforcement learning
Baolin Peng, Xiujun Li, Lihong Li, Jianfeng Gao, Asli Celikyilmaz, Sungjin Lee, and Kam-Fai Wong. 2017 · 2017
Cited alongside, same era.
Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017 · 2017
Cited alongside, same era.
Reward-balancing for statistical spoken dialogue systems using multi-objective reinforcement learning
Stefan Ultes, Paweł Budzianowski, Iñigo Casanueva, Nikola Mrkšić, Lina M Rojas Barahona, Pei-Hao Su, Tsung-Hsien Wen, Milica Gašić, and Steve Young. 2017 · 2017
Cited alongside, same era.
Sample efficient actor-critic with experience replay
Ziyu Wang, Victor Bapst, Nicolas Heess, Volodymyr Mnih, Remi Munos, Koray Kavukcuoglu, and Nando de Freitas. 2017 · 2017
Cited alongside, same era.
Bing Liu and Ian Lane. 2018 · 2018
Later among the works it cites.
Bootstrapping a neural conversational agent with dialogue self-play, crowdsourcing and on-line reinforcement learning
Pararth Shah, Dilek Hakkani-Tür, Bing Liu, and Gokhan Tür. 2018 · 2018
Later among the works it cites.
Sentiment adaptive end-to-end dialog systems
Weiyan Shi and Zhou Yu. 2018 · 2018
Later among the works it cites.
Discriminative deep dyna-q: Robust planning for dialogue policy learning
Shang-Yu Su, Xiujun Li, Jianfeng Gao, Jingjing Liu, and Yun-Nung Chen. 2018 · 2018
Later among the works it cites.
Hierarchical text generation and planning for strategic dialogue
Denis Yarats and Mike Lewis. 2018 · 2018
Later among the works it cites.
Convlab: Multi-domain end-to-end dialog system platform
Sungjin Lee, Qi Zhu, Ryuichi Takanobu, Zheng Zhang, Yaoqin Zhang, Xiang Li, Jinchao Li, Baolin Peng, Xiujun Li, Minlie Huang, and Jianfeng Gao. 2019 · 2019
Closest in time.
Memory-augmented dialogue management for task-oriented dialogue systems
Zheng Zhang, Minlie Huang, Zhongzhou Zhao, Feng Ji, Haiqing Chen, and Xiaoyan Zhu. 2019 · 2019
Closest in time.