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Goal-conditioned hierarchical reinforcement learning (HRL) is a promising approach for scaling up reinforcement learning (RL) techniques.
Improving generalization for temporal difference learning: The successor representation
Peter Dayan · 1993
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Feudal reinforcement learning
Peter Dayan and Geoffrey E Hinton · 1993
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Planning simple trajectories using neural subgoal generators
Jürgen Schmidhuber and Reiner Wahnsiedler · 1993
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Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning
Richard S. Sutton, Doina Precup, and Satinder Singh · 1999
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Temporal abstraction in reinforcement learning
Doina Precup · 2000
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Automatic discovery of subgoals in reinforcement learning using diverse density
Amy McGovern and Andrew G. Barto · 2001
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Recent advances in hierarchical reinforcement learning
Andrew G. Barto and Sridhar Mahadevan · 2003
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Metrics for finite Markov Decision Processes
Norm Ferns, Prakash Panangaden, and Doina Precup · 2004
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Identifying useful subgoals in reinforcement learning by local graph partitioning
Özgür Şimşek, Alicia P. Wolfe, and Andrew G. Barto · 2005
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Dimensionality reduction by learning an invariant mapping
R. Hadsell, S. Chopra, and Y. LeCun · 2006
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Mujoco: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
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Universal value function approximators
Tom Schaul, Daniel Horgan, Karol Gregor, and David Silver · 2015
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Benchmarking deep reinforcement learning for continuous control
Yan Duan, Xi Chen, Rein Houthooft, John Schulman, and Pieter Abbeel · 2016
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Hierarchical deep reinforcement learning: Integrating temporal abstraction and intrinsic motivation
Tejas D. Kulkarni, Karthik Narasimhan, Ardavan Saeedi, and Josh Tenenbaum · 2016
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Deep successor reinforcement learning
Tejas D. Kulkarni, Ardavan Saeedi, Simanta Gautam, and Samuel J. Gershman · 2016
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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
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Hindsight experience replay
Marcin Andrychowicz, Filip Wolski, Alex Ray, Jonas Schneider, Rachel Fong, Peter Welinder, Bob McGrew, Josh Tobin, Pieter Abbeel, and Wojciech Zaremba · 2017
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Stochastic neural networks for hierarchical reinforcement learning
Carlos Florensa, Yan Duan, and Pieter Abbeel · 2017
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Beta-VAE: Learning basic visual concepts with a constrained variational framework
Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matthew Botvinick, Shakir Mohamed, and Alexander Lerchner · 2017
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FeUdal networks for hierarchical reinforcement learning
Alexander Sasha Vezhnevets, Simon Osindero, Tom Schaul, Nicolas Heess, Max Jaderberg, David Silver, and Koray Kavukcuoglu · 2017
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Self-supervised learning of image embedding for continuous control
Carlos Florensa, Jonas Degrave, Nicolas Heess, Jost Tobias Springenberg, and Martin Riedmiller · 2019
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Mapping state space using landmarks for universal goal reaching
Zhiao Huang, Fangchen Liu, and Hao Su · 2019
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Learning multi-level hierarchies with hindsight
Andrew Levy, George Konidaris, Robert Platt, and Kate Saenko · 2019
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Near-optimal representation learning for hierarchical reinforcement learning
Ofir Nachum, Shixiang Gu, Honglak Lee, and Sergey Levine · 2019
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Why does hierarchy (sometimes) work so well in reinforcement learning?
Ofir Nachum, Haoran Tang, Xingyu Lu, Shixiang Gu, Honglak Lee, and Sergey Levine · 2019
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Carlos Florensa, David Held, Xinyang Geng, and Pieter Abbeel · 2018
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Data-efficient hierarchical reinforcement learning
Ofir Nachum, Shixiang Shane Gu, Honglak Lee, and Sergey Levine · 2018
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Visual reinforcement learning with imagined goals
Ashvin V Nair, Vitchyr Pong, Murtaza Dalal, Shikhar Bahl, Steven Lin, and Sergey Levine · 2018
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Temporal difference models: Model-free deep RL for model-based control
Vitchyr Pong, Shixiang Gu, Murtaza Dalal, and Sergey Levine · 2018
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Semi-parametric topological memory for navigation
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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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Planning with goal-conditioned policies
Soroush Nasiriany, Vitchyr H. Pong, Steven Lin, and Sergey Levine · 2019
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Unsupervised methods for subgoal discovery during intrinsic motivation in model-free hierarchical reinforcement learning
Jacob Rafati and David C Noelle · 2019
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Exploration via hindsight goal generation
Zhizhou Ren, Kefan Dong, Yuan Zhou, Qiang Liu, and Jian Peng · 2019
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Episodic curiosity through reachability
Nikolay Savinov, Anton Raichuk, Raphaël Marinier, Damien Vincent, Marc Pollefeys, Timothy Lillicrap, and Sylvain Gelly · 2019
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Scalable methods for computing state similarity in deterministic Markov Decision Processes
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