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Hierarchical reinforcement learning is a promising approach to tackle long-horizon decision-making problems with sparse rewards.
Self-supervised Learning of Image Embedding for Continuous Control
Carlos Florensa, Jonas Degrave, Nicolas Heess, Jost Tobias Springenberg, and Martin Riedmiller · 1901
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Credit Assignment Techniques in Stochastic Computation Graphs
Théophane Weber, Nicolas Heess, Lars Buesing, and David Silver · 1901
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MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies
Xue Bin Peng, Michael Chang, Grace Zhang, Pieter Abbeel, and Sergey Levine · 1905
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Reverse Curriculum Generation for Reinforcement Learning
Carlos Florensa, David Held, Markus Wulfmeier, Michael Zhang, and Pieter Abbeel · 1938
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Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
Ronald J Williams · 1992
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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, 1 2000
Doina Precup · 2000
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A Natural Policy Gradient
Sham Kakade · 2002
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Hierarchical Policy Gradient Algorithms
Mohammad Ghavamzadeh and Sridhar Mahadevan · 2003
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Natural Actor-Critic
Jan Peters and Stefan Schaal · 2007
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MuJoCo : A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
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Learning Stochastic Feedforward Neural Networks
Yichuan Tang and Ruslan Salakhutdinov · 2013
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei a Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, and Demis Hassabis · 2015
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Nonparametric Bayesian Reward Segmentation for Skill Discovery Using Inverse Reinforcement Learning
Pravesh Ranchod, Benjamin Rosman, and George Konidaris · 2015
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Trust Region Policy Optimization
John Schulman, Philipp Moritz, Michael Jordan, and Pieter Abbeel · 2015
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Probabilistic inference for determining options in reinforcement learning
Christian Daniel, Herke van Hoof, Jan Peters, Gerhard Neumann, Thomas Gärtner, Mirco Nanni, Andrea Passerini, and Celine B Robardet Christian Daniel ChristianDaniel · 2016
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Benchmarking Deep Reinforcement Learning for Continuous Control
Yan Duan, Xi Chen, John Schulman, and Pieter Abbeel · 2016
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Learning and Transfer of Modulated Locomotor Controllers
Nicolas Heess, Greg Wayne, Yuval Tassa, Timothy Lillicrap, Martin Riedmiller, David Silver, and Google Deepmind · 2016
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Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation
Tejas D Kulkarni, Karthik R Narasimhan, Ardavan Saeedi CSAIL, and Joshua B Tenenbaum BCS · 2016
Cited alongside, same era.
HIGH-DIMENSIONAL CONTINUOUS CONTROL USING GENERALIZED ADVANTAGE ESTIMATION
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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Meta Learning Shared Hierarchies
Kevin Frans, Jonathan Ho, Xi Chen, Pieter Abbeel, and John Schulman · 2018
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Latent Space Policies for Hierarchical Reinforcement Learning
Tuomas Haarnoja, Kristian Hartikainen, Pieter Abbeel, and Sergey Levine · 2018
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Learning an Embedding Space for Transferable Robot Skills
Karol Hausman, Jost Tobias Springenberg, Ziyu Wang, Nicolas Heess, and Martin Riedmiller · 2018
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Hierarchical Imitation and Reinforcement Learning
Hoang M Le, Nan Jiang, Alekh Agarwal, Miroslav Dud, and Yue Hal · 2018
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John Schulman, Philipp Moritz, Sergey Levine, Michael I Jordan, and Pieter Abbeel · 2016
Cited alongside, same era.
Hierarchical and interpretable skill acquisition in multi-task reinforcement Learning
Tianmin Shu, Caiming Xiong, and Richard Socher · 2016
Cited alongside, same era.
Strategic Attentive Writer for Learning Macro-Actions
Alexander Vezhnevets, Volodymyr Mnih, John Agapiou, Simon Osindero, Alex Graves, Oriol Vinyals, and Koray Kavukcuoglu Google DeepMind · 2016
Cited alongside, same era.
Modular Multitask Reinforcement Learning with Policy Sketches
Jacob Andreas, Dan Klein, and Sergey Levine · 2017
Cited alongside, same era.
The Option-Critic Architecture
Pierre-Luc Bacon, Jean Harb, and Doina Precup · 2017
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Feudal Reinforcement Learning
Peter Dayan and Geoffrey E. Hinton · 2017
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When Waiting is not an Option : Learning Options with a Deliberation Cost
Jean Harb, Pierre-Luc Bacon, Martin Klissarov, and Doina Precup · 2017
Cited alongside, same era.
Emergence of Locomotion Behaviours in Rich Environments
Nicolas Heess, Dhruva TB, Srinivasan Sriram, Jay Lemmon, Josh Merel, Greg Wayne, Yuval Tassa, Tom Erez, Ziyu Wang, S. M. Ali Eslami, Martin Riedmiller, and David Silver · 2017
Cited alongside, same era.
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Data-Efficient Hierarchical Reinforcement Learning
Ofir Nachum, Honglak Lee, Shane Gu, and Sergey Levine · 2018
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Visual Reinforcement Learning with Imagined Goals
Ashvin Nair, Vitchyr Pong, Murtaza Dalal, Shikhar Bahl, Steven Lin, and Sergey Levine · 2018
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Learning Dexterous In-Hand Manipulation
OpenAI, Marcin Andrychowicz, Bowen Baker, Maciek Chociej, Rafal Jozefowicz, Bob McGrew, Jakub Pachocki, Arthur Petron, Matthias Plappert, Glenn Powell, and Alex Ray · 2018
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Arjun Sharma, Mohit Sharma, Nicholas Rhinehart, and Kris M Kitani · 2018
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An inference-based policy gradient method for learning options, 2 2018
Matthew J. A. Smith, Herke van Hoof, and Joelle Pineau · 2018
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Multitask Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies
Sungryull Sohn, Junhyuk Oh, and Honglak Lee · 2018
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The Mirage of Action-Dependent Baselines in Reinforcement Learning
George Tucker, Surya Bhupatiraju, Shixiang Gu, Richard E Turner, Zoubin Ghahramani, and Sergey Levine · 2018
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Diversity is All You Need: Learning Skills without a Reward Function
Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, and Sergey Levine · 2019
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Hierarchical Reinforcement Learning with Hindsight
Andrew Levy, Robert Platt, and Kate Saenko · 2019
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Hierarchical visuomotor control of humanoids
Josh Merel, Arun Ahuja, Vu Pham, Saran Tunyasuvunakool, Siqi Liu, Dhruva Tirumala, Nicolas Heess, and Greg Wayne · 2019
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