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To assist with everyday human activities, robots must solve complex long-horizon tasks and generalize to new settings.
Pddl2. 1: An extension to pddl for expressing temporal planning domains
Maria Fox and Derek Long · 2003
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AprilTag: A robust and flexible visual fiducial system
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Logic-geometric programming: An optimization-based approach to combined task and motion planning
Marc Toussaint · 2015
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Sergey Levine, Chelsea Finn, Trevor Darrell, and Pieter Abbeel · 2016
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The option-critic architecture
Pierre-Luc Bacon, Jean Harb, and Doina Precup · 2017
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Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates
Shixiang Gu, Ethan Holly, Timothy Lillicrap, and Sergey Levine · 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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Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, and Sergey Levine · 2018
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From skills to symbols: Learning symbolic representations for abstract high-level planning
George Konidaris, Leslie Pack Kaelbling, and Tomas Lozano-Perez · 2018
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Neural task programming: Learning to generalize across hierarchical tasks
Danfei Xu, Suraj Nair, Yuke Zhu, Julian Gao, Animesh Garg, Li Fei-Fei, and Silvio Savarese · 2018
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David Abel, Nate Umbanhowar, Khimya Khetarpal, Dilip Arumugam, Doina Precup, and Michael Littman · 2020
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Sparse graphical memory for robust planning
Scott Emmons, Ajay Jain, Misha Laskin, Thanard Kurutach, Pieter Abbeel, and Deepak Pathak · 2020
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Accelerating robotic reinforcement learning via parameterized action primitives
Murtaza Dalal, Deepak Pathak, and Russ R Salakhutdinov · 2021
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Integrated task and motion planning
Caelan Reed Garrett, Rohan Chitnis, Rachel Holladay, Beomjoon Kim, Tom Silver, Leslie Pack Kaelbling, and Tomás Lozano-Pérez · 2021
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Autonomous reinforcement learning via subgoal curricula
Archit Sharma, Abhishek Gupta, Sergey Levine, Karol Hausman, and Chelsea Finn · 2021
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Learning symbolic operators for task and motion planning
Tom Silver, Rohan Chitnis, Joshua Tenenbaum, Leslie Pack Kaelbling, and Tomás Lozano-Pérez · 2021
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Deep affordance foresight: Planning through what can be done in the future
Danfei Xu, Ajay Mandlekar, Roberto Martín-Martín, Yuke Zhu, Silvio Savarese, and Li Fei-Fei · 2021
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Search-based task planning with learned skill effect models for lifelong robotic manipulation
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Kuan Fang, Yuke Zhu, Silvio Savarese, and L Fei-Fei · 2020
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Symbolic plans as high-level instructions for reinforcement learning
León Illanes, Xi Yan, Rodrigo Toro Icarte, and Sheila A McIlraith · 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
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robosuite: A modular simulation framework and benchmark for robot learning
Yuke Zhu, Josiah Wong, Ajay Mandlekar, and Roberto Martín-Martín · 2020
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Camps: Learning context-specific abstractions for efficient planning in factored mdps
Rohan Chitnis, Tom Silver, Beomjoon Kim, Leslie Kaelbling, and Tomas Lozano-Perez · 2021
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Jacky Liang, Mohit Sharma, Alex LaGrassa, Shivam Vats, Saumya Saxena, and Oliver Kroemer · 2022
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Augmenting reinforcement learning with behavior primitives for diverse manipulation tasks
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Learning neuro-symbolic skills for bilevel planning
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Jump-start reinforcement learning
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Predicate invention for bilevel planning
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