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Some Learning from Demonstrations (LfD) methods handle small mismatches in the action spaces of the teacher and student.
Mathematical programs with equilibrium constraints
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Learning rhythmic movements by demonstration using nonlinear oscillators
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A tutorial on the cross-entropy method
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Batch reinforcement learning
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A direct method for trajectory optimization of rigid bodies through contact
M. Posa, C. Cantu, and R. Tedrake · 2014
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Robot learning manipulation action plans by “watching” unconstrained videos from the world wide web
Y. Yang, Y. Li, C. Fermuller, and Y. Aloimonos · 2015
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Generative adversarial imitation learning
J. Ho and S. Ermon · 2016
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Xpbd: position-based simulation of compliant constrained dynamics
M. Macklin, M. Müller, and N. Chentanez · 2016
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Aggressive driving with model predictive path integral control
G. Williams, P. Drews, B. Goldfain, J. M. Rehg, and E. A. Theodorou · 2016
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One-shot visual imitation learning via meta-learning
C. Finn, T. Yu, T. Zhang, P. Abbeel, and S. Levine · 2017
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One-shot imitation learning
Y. Duan, M. Andrychowicz, B. Stadie, J. Ho, J. Schneider, I. Sutskever, P. Abbeel, and W. Zaremba · 2017
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DART: noise injection for robust imitation learning
M. Laskey, J. Lee, R. Fox, A. D. Dragan, and K. Goldberg · 2017
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Leveraging demonstrations for deep reinforcement learning on robotics problems with sparse rewards
M. Vecerík, T. Hester, J. Scholz, F. Wang, O. Pietquin, B. Piot, N. M. O. Heess, T. Rothörl, T. Lampe, and M. A. Riedmiller · 2017
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An introduction to trajectory optimization: How to do your own direct collocation
M. Kelly · 2017
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Information theoretic mpc for model-based reinforcement learning
G. Williams, N. Wagener, B. Goldfain, P. Drews, J. M. Rehg, B. Boots, and E. A. Theodorou · 2017
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Improved learning of dynamics models for control
A. Venkatraman, R. Capobianco, L. Pinto, M. Hebert, D. Nardi, and J. A. Bagnell · 2017
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Learning dynamic models for open loop predictive control of soft robotic manipulators
T. G. Thuruthel, E. Falotico, F. Renda, and C. Laschi · 2017
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Survey of model-based reinforcement learning: Applications on robotics
A. S. Polydoros and L. Nalpantidis · 2017
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Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
T. Haarnoja, A. Zhou, P. Abbeel, and S. Levine · 2018
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Zero-shot visual imitation
D. Pathak, P. Mahmoudieh, G. Luo, P. Agrawal, D. Chen, Y. Shentu, E. Shelhamer, J. Malik, A. A. Efros, and T. Darrell · 2018
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Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations
A. Rajeswaran, V. Kumar, A. Gupta, G. Vezzani, J. Schulman, E. Todorov, and S. Levine · 2018
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Behavioral cloning from observation
F. Torabi, G. Warnell, and P. Stone · 2018
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Generative adversarial imitation from observation
F. Torabi, G. Warnell, and P. Stone · 2018
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Deepmimic: Example-guided deep reinforcement learning of physics-based character skills
X. B. Peng, P. Abbeel, S. Levine, and M. van de Panne · 2018
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Sim-to-real reinforcement learning for deformable object manipulation
State-only imitation learning for dexterous manipulation
I. Radosavovic, X. Wang, L. Pinto, and J. Malik · 2021
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Trajectory optimization for manipulation of deformable objects: Assembly of belt drive units
S. Jin, D. Romeres, A. Ragunathan, D. K. Jha, and M. Tomizuka · 2021
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Super-human performance in gran turismo sport using deep reinforcement learning
F. Fuchs, Y. Song, E. Kaufmann, D. Scaramuzza, and P. Dürr · 2021
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Bridging offline reinforcement learning and imitation learning: A tale of pessimism
P. Rashidinejad, B. Zhu, C. Ma, J. Jiao, and S. Russell · 2021
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Xirl: Cross-embodiment inverse reinforcement learning
K. Zakka, A. Zeng, P. Florence, J. Tompson, J. Bohg, and D. Dwibedi · 2021
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Generalizable imitation learning from observation via inferring goal proximity
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J. Matas, S. James, and A. J. Davison · 2018
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Trajectory optimization for cable-driven soft robot locomotion
J. M. Bern, P. Banzet, R. Poranne, and S. Coros · 2019
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Scaling robot supervision to hundreds of hours with roboturk: Robotic manipulation dataset through human reasoning and dexterity
A. Mandlekar, J. Booher, M. Spero, A. Tung, A. Gupta, Y. Zhu, A. Garg, S. Savarese, and L. Fei-Fei · 2019
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Recent advances in imitation learning from observation
F. Torabi, G. Warnell, and P. Stone · 2019
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Learning latent dynamics for planning from pixels
D. Hafner, T. Lillicrap, I. Fischer, R. Villegas, D. Ha, H. Lee, and J. Davidson · 2019
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Offline reinforcement learning: Tutorial, review, and perspectives on open problems
S. Levine, A. Kumar, G. Tucker, and J. Fu · 2020
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Conservative q-learning for offline reinforcement learning
A. Kumar, A. Zhou, G. Tucker, and S. Levine · 2020
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Y. Lee, A. Szot, S.-H. Sun, and J. J. Lim · 2021
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Image augmentation is all you need: Regularizing deep reinforcement learning from pixels
D. Yarats, I. Kostrikov, and R. Fergus · 2021
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Perceiver io: A general architecture for structured inputs & outputs
A. Jaegle, S. Borgeaud, J.-B. Alayrac, C. Doersch, C. Ionescu, D. Ding, S. Koppula, D. Zoran, A. Brock, E. Shelhamer, et al · 2021
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Distilling motion planner augmented policies into visual control policies for robot manipulation
I.-C. A. Liu, S. Uppal, G. S. Sukhatme, J. J. Lim, P. Englert, and Y. Lee · 2022
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Learning visual feedback control for dynamic cloth folding
J. Hietala, D. Blanco–Mulero, G. Alcan, and V. Kyrki · 2022
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Learning periodic tasks from human demonstrations
J. Yang, J. Zhang, C. Settle, A. Rai, R. Antonova, and J. Bohg · 2022
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Daydreamer: World models for physical robot learning
P. Wu, A. Escontrela, D. Hafner, K. Goldberg, and P. Abbeel · 2022
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Learning deformable object manipulation from expert demonstrations
G. Salhotra, I.-C. A. Liu, M. Dominguez-Kuhne, and G. S. Sukhatme · 2022
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Rt-1: Robotics transformer for real-world control at scale
A. Brohan, N. Brown, J. Carbajal, Y. Chebotar, J. Dabis, C. Finn, K. Gopalakrishnan, K. Hausman, A. Herzog, J. Hsu, et al · 2022
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Learning visible connectivity dynamics for cloth smoothing
X. Lin, Y. Wang, Z. Huang, and D. Held · 2022
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Mesh-based Dynamics with Occlusion Reasoning for Cloth Manipulation
Z. Huang, X. Lin, and D. Held · 2022
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Ls-iq: Implicit reward regularization for inverse reinforcement learning
F. Al-Hafez, D. Tateo, O. Arenz, G. Zhao, and J. Peters · 2023
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Learning by watching via keypoint extraction and imitation learning
Y.-T. A. Sun, H.-C. Lin, P.-Y. Wu, and J.-T. Huang · 2075
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