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Text Worlds are virtual environments for embodied agents that, unlike 2D or 3D environments, are rendered exclusively using textual descriptions.
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Human-level control through deep reinforcement learning
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Learning to speak and act in a fantasy text adventure game
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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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Deep reinforcement learning with a combinatorial action space for predicting popular Reddit threads
Ji He, Mari Ostendorf, Xiaodong He, Jianshu Chen, Jianfeng Gao, Lihong Li, and Li Deng. 2016b · 2016
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The malmo platform for artificial intelligence experimentation
Matthew Johnson, Katja Hofmann, Tim Hutton, and David Bignell. 2016 · 2016
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Anna-Lisa Vollmer, Britta Wrede, Katharina J Rohlfing, and Pierre-Yves Oudeyer. 2016 · 2016
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Learning to speak and act in a fantasy text adventure game
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Experience grounds language
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RoboTHOR: An Open Simulation-to-Real Embodied AI Platform
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Interactive fiction game playing as multi-paragraph reading comprehension with reinforcement learning
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Interactive fiction games: A colossal adventure
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Algorithmic improvements for deep reinforcement learning applied to interactive fiction
Vishal Jain, William Fedus, Hugo Larochelle, Doina Precup, and Marc G Bellemare. 2020 · 2020
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Visually-grounded planning without vision: Language models infer detailed plans from high-level instructions
Peter Jansen. 2020 · 2020
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Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Joey Tianyi Zhou, and Chengqi Zhang. 2020 · 2020
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