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Text adventure games present unique challenges to reinforcement learning methods due to their combinatorially large action spaces and sparse rewards.
R-max-a general polynomial time algorithm for near-optimal reinforcement learning
Ronen I Brafman and Moshe Tennenholtz · 2002
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Near-optimal reinforcement learning in polynomial time
Michael Kearns and Satinder Singh · 2002
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Mujoco: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
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The arcade learning environment: An evaluation platform for general agents
Marc G Bellemare, Yavar Naddaf, Joel Veness, and Michael Bowling · 2013
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Language understanding for text-based games using deep reinforcement learning
Karthik Narasimhan, Tejas Kulkarni, and Regina Barzilay · 2015
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Tom Schaul, John Quan, Ioannis Antonoglou, and David Silver · 2015
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Unifying count-based exploration and intrinsic motivation
Marc Bellemare, Sriram Srinivasan, Georg Ostrovski, Tom Schaul, David Saxton, and Remi Munos · 2016
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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
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Curiosity-driven exploration by self-supervised prediction
Deepak Pathak, Pulkit Agrawal, Alexei A Efros, and Trevor Darrell · 2017
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# exploration: A study of count-based exploration for deep reinforcement learning
Haoran Tang, Rein Houthooft, Davis Foote, Adam Stooke, Xi Chen, Yan Duan, John Schulman, Filip De Turck, and Pieter Abbeel · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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GEP-PG: Decoupling exploration and exploitation in deep reinforcement learning algorithms
Cédric Colas, Olivier Sigaud, and Pierre-Yves Oudeyer · 2018
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Textworld: A learning environment for text-based games
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
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An introduction to deep reinforcement learning
Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G Bellemare, and Joelle Pineau · 2018
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Self-imitation learning
Junhyuk Oh, Yijie Guo, Satinder Singh, and Honglak Lee · 2018
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Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto · 2018
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Counting to explore and generalize in text-based games
Xingdi Yuan, Marc-Alexandre Côté, Alessandro Sordoni, Romain Laroche, Remi Tachet des Combes, Matthew J. Hausknecht, and Adam Trischler · 2018
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Learn what not to learn: Action elimination with deep reinforcement learning
Tom Zahavy, Matan Haroush, Nadav Merlis, Daniel J. Mankowitz, and Shie Mannor · 2018
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Playing text-adventure games with graph-based deep reinforcement learning
Prithviraj Ammanabrolu and Mark Riedl · 2019
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Nail: A general interactive fiction agent
Matthew Hausknecht, Ricky Loynd, Greg Yang, Adith Swaminathan, and Jason D Williams · 2019
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Explicit explore-exploit algorithms in continuous state spaces
Mikael Henaff · 2019
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Monte-carlo planning and learning with language action value estimates
Youngsoo Jang, Seokin Seo, Jongmin Lee, and Kee-Eung Kim · 2020
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Random curiosity-driven exploration in deep reinforcement learning
Jing Li, Xinxin Shi, Jiehao Li, Xin Zhang, and Junzheng Wang · 2020
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Count-based exploration with the successor representation
Marlos C. Machado, Marc G. Bellemare, and Michael Bowling · 2020
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Exploration based language learning for text-based games
Andrea Madotto, Mahdi Namazifar, Joost Huizinga, Piero Molino, Adrien Ecoffet, Huaixiu Zheng, Alexandros Papangelis, Dian Yu, Chandra Khatri, and Gökhan Tür · 2020
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Deep reinforcement learning with stacked hierarchical attention for text-based games
Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Joey Tianyi Zhou, and Chengqi Zhang · 2020
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Language models are unsupervised multitask learners, 2019
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2019
Cited alongside, same era.
Exploration conscious reinforcement learning revisited
Lior Shani, Yonathan Efroni, and Shie Mannor · 2019
Cited alongside, same era.
Learning dynamic knowledge graphs to generalize on text-based games
Ashutosh Adhikari, Xingdi (Eric) Yuan, Marc-Alexandre Côté, Mikulas Zelinka, Marc-Antoine Rondeau, Romain Laroche, Pascal Poupart, Jian Tang, Adam Trischler, and William L. Hamilton · 2020
Cited alongside, same era.
Pc-pg: Policy cover directed exploration for provable policy gradient learning
Alekh Agarwal, Mikael Henaff, Sham Kakade, and Wen Sun · 2020
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Graph constrained reinforcement learning for natural language action spaces
Prithviraj Ammanabrolu and Matthew J. Hausknecht · 2020
Cited alongside, same era.
How to avoid being eaten by a grue: Exploration strategies for text-adventure agents
Prithviraj Ammanabrolu, Ethan Tien, Zhaochen Luo, and Mark O Riedl · 2020
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Never give up: Learning directed exploration strategies
Adrià Puigdomènech Badia, Pablo Sprechmann, Alex Vitvitskyi, Daniel Guo, Bilal Piot, Steven Kapturowski, Olivier Tieleman, Martin Arjovsky, Alexander Pritzel, Andrew Bolt, et al · 2020
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Shunyu Yao, Rohan Rao, Matthew Hausknecht, and Karthik Narasimhan · 2020
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Deep reinforcement learning at the edge of the statistical precipice
Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C Courville, and Marc Bellemare · 2021
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First return, then explore
Adrien Ecoffet, Joost Huizinga, Joel Lehman, Kenneth O Stanley, and Jeff Clune · 2021
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Emphatic algorithms for deep reinforcement learning
Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, and Hado Van Hasselt · 2021
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A survey of text games for reinforcement learning informed by natural language
Philip Osborne, Heido Nõmm, and Andre Freitas · 2021
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Decoupling exploration and exploitation in reinforcement learning
Lukas Schäfer, Filippos Christianos, Josiah Hanna, and Stefano V. Albrecht · 2021
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On bonus-based exploration methods in the arcade learning environment
Adrien Ali Taiga, William Fedus, Marlos C Machado, Aaron Courville, and Marc G Bellemare · 2021
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Decoupled exploration and exploitation policies for sample-efficient reinforcement learning
William F. Whitney, Michael Bloesch, Jost Tobias Springenberg, Abbas Abdolmaleki, and Martin A. Riedmiller · 2021
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Generalization in text-based games via hierarchical reinforcement learning
Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, and Chengqi Zhang · 2021
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Reading and acting while blindfolded: The need for semantics in text game agents
Shunyu Yao, Karthik Narasimhan, and Matthew Hausknecht · 2021
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