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Defining action spaces for conversational agents and optimizing their decision-making process with reinforcement learning is an enduring challenge.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams. 1992 · 1992
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Reinforcement learning: A survey
Leslie Pack Kaelbling, Michael L Littman, and Andrew W Moore. 1996 · 1996
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An application of reinforcement learning to dialogue strategy selection in a spoken dialogue system for email
Marilyn A. Walker. 2000 · 2000
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Variance reduction techniques for gradient estimates in reinforcement learning
Evan Greensmith, Peter L Bartlett, and Jonathan Baxter. 2004 · 2004
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Let’s go public! taking a spoken dialog system to the real world
Antoine Raux, Brian Langner, Dan Bohus, Alan W Black, and Maxine Eskenazi. 2005 · 2005
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Using pomdps for dialog management
Steve J Young. 2006 · 2006
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Partially observable markov decision processes for spoken dialog systems
Jason D Williams and Steve Young. 2007 · 2007
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The hidden information state approach to dialog management
Stephanie Young, Jost Schatzmann, Karl Weilhammer, and Hui Ye. 2007 · 2007
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The epoch-greedy algorithm for multi-armed bandits with side information
John Langford and Tong Zhang. 2008 · 2008
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Unsupervised induction and filling of semantic slots for spoken dialogue systems using frame-semantic parsing
Yun-Nung Chen, William Yang Wang, and Alexander I Rudnicky. 2013 · 2013
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling. 2013 · 2013
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Structured discriminative model for dialog state tracking
Sungjin Lee. 2013 · 2013
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Pomdp-based statistical spoken dialog systems: A review
Steve Young, Milica Gašić, Blaise Thomson, and Jason D Williams. 2013 · 2013
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Learning phrase representations using rnn encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014
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Gaussian processes for pomdp-based dialogue manager optimization
Milica Gasic and Steve Young. 2014 · 2014
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Word-based dialog state tracking with recurrent neural networks
Matthew Henderson, Blaise Thomson, and Steve Young. 2014 · 2014
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Effective approaches to attention-based neural machine translation
Thang Luong, Hieu Pham, and Christopher D Manning. 2015 · 2015
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A neural network approach to context-sensitive generation of conversational responses
Alessandro Sordoni, Michel Galley, Michael Auli, Chris Brockett, Yangfeng Ji, Margaret Mitchell, Jian-Yun Nie, Jianfeng Gao, and Bill Dolan. 2015 · 2015
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Oriol Vinyals and Quoc Le. 2015 · 2015
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Categorical reparameterization with gumbel-softmax
Eric Jang, Shixiang Gu, and Ben Poole. 2016 · 2016
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Natural language does not emerge ‘naturally’in multi-agent dialog
Satwik Kottur, José Moura, Stefan Lee, and Dhruv Batra. 2017 · 2017
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Deal or no deal? end-to-end learning of negotiation dialogues
Mike Lewis, Denis Yarats, Yann Dauphin, Devi Parikh, and Dhruv Batra. 2017 · 2017
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An end-to-end trainable neural network model with belief tracking for task-oriented dialog
Bing Liu and Ian Lane. 2017 · 2017
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Emergence of grounded compositional language in multi-agent populations
Igor Mordatch and Pieter Abbeel. 2017 · 2017
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Sample-efficient actor-critic reinforcement learning with supervised data for dialogue management
Pei-Hao Su, Paweł Budzianowski, Stefan Ultes, Milica Gasic, and Steve Young. 2017 · 2017
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Deep reinforcement learning for dialogue generation
Jiwei Li, Will Monroe, Alan Ritter, Dan Jurafsky, Michel Galley, and Jianfeng Gao. 2016 · 2016
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Building end-to-end dialogue systems using generative hierarchical neural network models
Iulian V Serban, Alessandro Sordoni, Yoshua Bengio, Aaron Courville, and Joelle Pineau. 2016 · 2016
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A network-based end-to-end trainable task-oriented dialogue system
Tsung-Hsien Wen, Milica Gasic, Nikola Mrksic, Lina M Rojas-Barahona, Pei-Hao Su, Stefan Ultes, David Vandyke, and Steve Young. 2016 · 2016
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End-to-end lstm-based dialog control optimized with supervised and reinforcement learning
Jason D Williams and Geoffrey Zweig. 2016 · 2016
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Hierarchical attention networks for document classification
Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola, and Eduard Hovy. 2016 · 2016
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Towards end-to-end learning for dialog state tracking and management using deep reinforcement learning
Tiancheng Zhao and Maxine Eskenazi. 2016 · 2016
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Latent variable dialogue models and their diversity
Kris Cao and Stephen Clark. 2017 · 2017
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Latent intention dialogue models
Tsung-Hsien Wen, Yishu Miao, Phil Blunsom, and Steve Young. 2017 · 2017
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Hybrid code networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning
Jason D Williams, Kavosh Asadi, and Geoffrey Zweig. 2017 · 2017
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Hierarchical text generation and planning for strategic dialogue
Denis Yarats and Mike Lewis. 2017 · 2017
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Learning discourse-level diversity for neural dialog models using conditional variational autoencoders
Tiancheng Zhao, Ran Zhao, and Maxine Eskenazi. 2017 · 2017
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Multiwoz-a large-scale multi-domain wizard-of-oz dataset for task-oriented dialogue modelling
Paweł Budzianowski, Tsung-Hsien Wen, Bo-Hsiang Tseng, Iñigo Casanueva, Stefan Ultes, Osman Ramadan, and Milica Gasic. 2018 · 2018
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Decoupling strategy and generation in negotiation dialogues
He He, Derek Chen, Anusha Balakrishnan, and Percy Liang. 2018 · 2018
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Towards universal dialogue state tracking
Liliang Ren, Kaige Xie, Lu Chen, and Kai Yu. 2018 · 2018
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Zero-shot dialog generation with cross-domain latent actions
Tiancheng Zhao and Maxine Eskenazi. 2018 · 2018
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Unsupervised discrete sentence representation learning for interpretable neural dialog generation
Tiancheng Zhao, Kyusong Lee, and Maxine Eskenazi. 2018 · 2018
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