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Text adventure games, in which players must make sense of the world through text descriptions and declare actions through text descriptions, provide a stepping stone toward grounding action in language.
Nail: A general interactive fiction agent
Matthew Hausknecht, Ricky Loynd, Greg Yang, Adith Swaminathan, and Jason D. Williams. 2019 · 1902
Earlier work this paper cites.
Reinforcement learning for robots using neural networks
Long-Ji Lin. 1993 · 1993
Earlier work this paper cites.
Value-function-based transfer for reinforcement learning using structure mapping
Yaxin Liu and Peter Stone. 2006 · 2006
Earlier work this paper cites.
Building portable options: Skill transfer in reinforcement learning
George Konidaris and Andrew G. Barto. 2007 · 2007
Earlier work this paper cites.
Transferring instances for model-based reinforcement learning
Matthew E. Taylor, Nicholas K. Jong, and Peter Stone. 2008 · 2008
Earlier work this paper cites.
Transfer learning for reinforcement learning domains: A survey
Matthew E. Taylor and Peter Stone. 2009 · 2009
Earlier work this paper cites.
Towards understanding situated natural language
Antoine Bordes, Nicolas Usunier, Ronan Collobert, and Jason Weston. 2010 · 2010
Earlier work this paper cites.
Transfer in reinforcement learning via shared features
George Konidaris, Ilya Scheidwasser, and Andrew G. Barto. 2012 · 2012
Earlier work this paper cites.
Transferring expectations in model-based reinforcement learning
Trung Thanh Nguyen, Tomi Silander, and Tze-Yun Leong. 2012 · 2012
Earlier work this paper cites.
Pomdp-based dialogue manager adaptation to extended domains
Milica Gasic, Catherine Breslin, Matthew Henderson, Dongho Kim, Martin Szummer, Blaise Thomson, Pirros Tsiakoulis, and Steve J. Young. 2013 · 2013
Earlier work this paper cites.
Leveraging Linguistic Structure For Open Domain Information Extraction
Gabor Angeli, Johnson Premkumar, Melvin Jose, and Christopher D. Manning. 2015 · 2015
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Language Understanding for Text-based Games Using Deep Reinforcement Learning
Karthik Narasimhan, Tejas Kulkarni, and Regina Barzilay. 2015 · 2015
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Learning domain-independent dialogue policies via ontology parameterisation
Zhuoran Wang, Tsung-Hsien Wen, Pei hao Su, and Yannis Stylianou. 2015 · 2015
Cited alongside, same era.
Deep Reinforcement Learning with a Natural Language Action Space
Ji He, Jianshu Chen, Xiaodong He, Jianfeng Gao, Lihong Li, Li Deng, and Mari Ostendorf. 2016 · 2016
Cited alongside, same era.
Actor-mimic: Deep multitask and transfer reinforcement learning
Emilio Parisotto, Jimmy Ba, and Ruslan R. Salakhutdinov. 2016 · 2016
Cited alongside, same era.
Knowledge transfer for deep reinforcement learning with hierarchical experience replay
H. Yin and S. J. Pan. 2017 · 2017
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TextWorld : A Learning Environment for Text-based Games
Marc-Alexandre Côté, Ákos Kádár, Xingdi Yuan, Ben Kybartas, Emery Fine, James Moore, Matthew Hausknecht, Layla El Asri, Mahmoud Adada, Wendy Tay, and Adam Trischler. 2018 · 2018
Later among the works it cites.
Learning How Not to Act in Text-Based Games
Matan Haroush, Tom Zahavy, Daniel J Mankowitz, and Shie Mannor. 2018 · 2018
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Jericho: A learning environment for man-made interactive fiction games
Matthew Hausknecht. 2018 · 2018
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Cross-domain transfer in reinforcement learning using target apprentice
Girish Joshi and Girish Chowdhary. 2018 · 2018
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Reinforcement Learning: An Introduction
Richard S Sutton and Andrew G Barto. 2018 · 2018
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Andrei A. Rusu, Neil C. Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, and Raia Hadsell. 2016 · 2016
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Reading Wikipedia to answer open-domain questions
Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes. 2017 · 2017
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What can you do with a rock? affordance extraction via word embeddings
Nancy Fulda, Daniel Ricks, Ben Murdoch, and David Wingate. 2017 · 2017
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Deep transfer in reinforcement learning by language grounding
Karthik Narasimhan, Regina Barzilay, and Tommi Jaakkola. 2017 · 2017
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Attend, adapt and transfer: Attentive deep architecture for adaptive transfer from multiple sources in the same domain
Janarthanan Rajendran, Aravind S. Lakshminarayanan, Mitesh M. Khapra, P. Prasanna, and Balaraman Ravindran. 2017 · 2017
Cited alongside, same era.
Later among the works it cites.
Towards solving text-based games by producing adaptive action spaces
Ruo Yu Tao, Marc-Alexandre Côté, Xingdi Yuan, and Layla El Asri. 2018 · 2018
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Playing text-adventure games with graph-based deep reinforcement learning
Prithviraj Ammanabrolu and Mark O. Riedl. 2019 · 2019
Closest in time.
Deep reinforcement learning with relational inductive biases
Vinicius Zambaldi, David Raposo, Adam Santoro, Victor Bapst, Yujia Li, Igor Babuschkin, Karl Tuyls, David Reichert, Timothy Lillicrap, Edward Lockhart, Murray Shanahan, Victoria Langston, Razvan Pascanu, Matthew Botvinick, Oriol Vinyals, and Peter Battaglia. 2019 · 2019
Closest in time.