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We teach goal-driven agents to interactively act and speak in situated environments by training on generated curriculums.
Countering language drift via visual grounding
Jason Lee, Kyunghyun Cho, and Douwe Kiela. 2019 · 1909
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Automated curricula through setter-solver interactions
Sebastien Racaniere, Andrew K Lampinen, Adam Santoro, David P Reichert, Vlad Firoiu, and Timothy P Lillicrap. 2019 · 1909
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Sebastian Risi and Julian Togelius. 2019 · 1911
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Asynchronous methods for deep reinforcement learning
Volodymyr Mnih, Adria Puigdomenech Badia, Mehdi Mirza, Alex Graves, Timothy Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu. 2016 · 1937
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Reinforcement learning for spoken dialogue systems
Satinder P Singh, Michael J Kearns, Diane J Litman, and Marilyn A Walker. 2000 · 2000
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Smote: synthetic minority over-sampling technique
Nitesh V Chawla, Kevin W Bowyer, Lawrence O Hall, and W Philip Kegelmeyer. 2002 · 2002
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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Shrimai Prabhumoye, Margaret Li, Jack Urbanek, Emily Dinan, Douwe Kiela, Jason Weston, and Arthur Szlam. 2020 · 2002
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Recipes for building an open-domain chatbot
Stephen Roller, Emily Dinan, Naman Goyal, Da Ju, Mary Williamson, Yinhan Liu, Jing Xu, Myle Ott, Kurt Shuster, Eric M Smith, et al. 2020 · 2004
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Enhancing text-based reinforcement learning agents with commonsense knowledge
Keerthiram Murugesan, Mattia Atzeni, Pushkar Shukla, Mrinmaya Sachan, Pavan Kapanipathi, and Kartik Talamadupula. 2020 · 2005
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Grounded cognition
Lawrence W. Barsalou. 2008 · 2008
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Curriculum learning
Yoshua Bengio, Jérôme Louradour, Ronan Collobert, and Jason Weston. 2009 · 2009
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Sample-efficient batch reinforcement learning for dialogue management optimization
Olivier Pietquin, Matthieu Geist, Senthilkumar Chandramohan, and Hervé Frezza-Buet. 2011 · 2011
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Factored markov decision processes
Thomas Degris and Olivier Sigaud. 2013 · 2013
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Powerplay: Training an increasingly general problem solver by continually searching for the simplest still unsolvable problem
Jürgen Schmidhuber. 2013 · 2013
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Policy networks with two-stage training for dialogue systems
Mehdi Fatemi, Layla El Asri, Hannes Schulz, Jing He, and Kaheer Suleman. 2016 · 2016
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Deep reinforcement learning for dialogue generation
Jiwei Li, Will Monroe, Alan Ritter, Michel Galley, Jianfeng Gao, and Dan Jurafsky. 2016 · 2016
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Automated curriculum learning for neural networks
Alex Graves, Marc G Bellemare, Jacob Menick, Rémi Munos, and Koray Kavukcuoglu. 2017 · 2017
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Deal or no deal? end-to-end learning for negotiation dialogues
Mike Lewis, Denis Yarats, Yann N Dauphin, Devi Parikh, and Dhruv Batra. 2017 · 2017
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Procedural generation in game design
Tanya Short and Tarn Adams. 2017 · 2017
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Knowledge graph embedding: A survey of approaches and applications
Q. Wang, Z. Mao, B. Wang, and L. Guo. 2017 · 2017
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Hierarchical text generation and planning for strategic dialogue
Denis Yarats and Mike Lewis. 2017 · 2017
Cited alongside, same era.
Experience grounds language
Yonatan Bisk, Ari Holtzman, Jesse Thomason, Jacob Andreas, Yoshua Bengio, Joyce Chai, Mirella Lapata, Angeliki Lazaridou, Jonathan May, Aleksandr Nisnevich, Nicolas Pinto, and Joseph Turian. 2020 · 2020
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Emergent complexity and zero-shot transfer via unsupervised environment design
Michael Dennis, Natasha Jaques, Eugene Vinitsky, Alexandre Bayen, Stuart Russell, Andrew Critch, and Sergey Levine. 2020 · 2020
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Queens are powerful too: Mitigating gender bias in dialogue generation
Emily Dinan, Angela Fan, Adina Williams, Jack Urbanek, Douwe Kiela, and Jason Weston. 2020 · 2020
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Interactive fiction games: A colossal adventure
Matthew Hausknecht, Prithviraj Ammanabrolu, Marc-Alexandre Côté, and Xingdi Yuan. 2020 · 2020
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Poly-encoders: Architectures and pre-training strategies for fast and accurate multi-sentence scoring
Samuel Humeau, Kurt Shuster, Marie-Anne Lachaux, and Jason Weston. 2020 · 2020
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Marc-Alexandre Côté, Ákos Kádár, Xingdi Yuan, Ben Kybartas, Tavian Barnes, Emery Fine, James Moore, Matthew Hausknecht, Layla El Asri, Mahmoud Adada, Wendy Tay, and Adam Trischler. 2018 · 2018
Cited alongside, same era.
BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Cited alongside, same era.
Illuminating generalization in deep reinforcement learning through procedural level generation
Niels Justesen, Ruben Rodriguez Torrado, Philip Bontrager, Ahmed Khalifa, Julian Togelius, and Sebastian Risi. 2018 · 2018
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Training millions of personalized dialogue agents
Pierre-Emmanuel Mazaré, Samuel Humeau, Martin Raison, and Antoine Bordes. 2018 · 2018
Cited alongside, same era.
Intrinsic motivation and automatic curricula via asymmetric self-play
Sainbayar Sukhbaatar, Zeming Lin, Ilya Kostrikov, Gabriel Synnaeve, Arthur Szlam, and Rob Fergus. 2018 · 2018
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Starspace: Embed all the things!
Ledell Wu, Adam Fisch, Sumit Chopra, Keith Adams, Antoine Bordes, and Jason Weston. 2018 · 2018
Cited alongside, same era.
Learning semantic textual similarity from conversations
Yinfei Yang, Steve Yuan, Daniel Cer, Sheng-Yi Kong, Noah Constant, Petr Pilar, Heming Ge, Yun-Hsuan Sung, Brian Strope, and Ray Kurzweil. 2018 · 2018
Cited alongside, same era.
Later among the works it cites.
Pcgrl: Procedural content generation via reinforcement learning
Ahmed Khalifa, Philip Bontrager, Sam Earle, and Julian Togelius. 2020 · 2020
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The NetHack Learning Environment
Heinrich Küttler, Nantas Nardelli, Alexander H. Miller, Roberta Raileanu, Marco Selvatici, Edward Grefenstette, and Tim Rocktäschel. 2020 · 2020
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BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
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Curriculum learning for reinforcement learning domains: A framework and survey
Sanmit Narvekar, Bei Peng, Matteo Leonetti, Jivko Sinapov, Matthew E Taylor, and Peter Stone. 2020 · 2020
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Teacher algorithms for curriculum learning of deep rl in continuously parameterized environments
Rémy Portelas, Cédric Colas, Katja Hofmann, and Pierre-Yves Oudeyer. 2020 · 2020
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State Prediction in TextWorld with a Predicate-Logic Pointer Network Architecture
Corentin Sautier, Don Joven Agravante, and Michiaki Tatsubori. 2020 · 2020
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Situated language learning via interactive narratives
Prithviraj Ammanabrolu and Mark O Riedl. 2021 · 2021
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How to motivate your dragon: Teaching goal-driven agents to speak and act in fantasy worlds
Prithviraj Ammanabrolu, Jack Urbanek, Margaret Li, Arthur Szlam, Tim Rocktäschel, and Jason Weston. 2021 · 2021
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Learning with {amig}o: Adversarially motivated intrinsic goals
Andres Campero, Roberta Raileanu, Heinrich Kuttler, Joshua B. Tenenbaum, Tim Rocktäschel, and Edward Grefenstette. 2021 · 2021
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Monte-carlo planning and learning with language action value estimates
Youngsoo Jang, Seokin Seo, Jongmin Lee, and Kee-Eung Kim. 2021 · 2021
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Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines
Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi, Pushkar Shukla, Sadhana Kumaravel, Gerald Tesauro, Kartik Talamadupula, Mrinmaya Sachan, and Murray Campbell. 2021 · 2021
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Minihack the planet: A sandbox for open-ended reinforcement learning research
Mikayel Samvelyan, Robert Kirk, Vitaly Kurin, Jack Parker-Holder, Minqi Jiang, Eric Hambro, Fabio Petroni, Heinrich Kuttler, Edward Grefenstette, and Tim Rocktäschel. 2021 · 2021
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Leveraging procedural generation to benchmark reinforcement learning
Karl Cobbe, Chris Hesse, Jacob Hilton, and John Schulman. 2020 · 2056
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