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Human demonstration videos are a widely available data source for robot learning and an intuitive user interface for expressing desired behavior.
Between mdps and semi-mdps: A framework for temporal abstraction in reinforcement learning
R. S. Sutton, D. Precup, and S. Singh · 1999
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A survey of robot learning from demonstration
B. Argall, S. Chernova, M. M. Veloso, and B. Browning · 2009
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Skill discovery in continuous reinforcement learning domains using skill chaining
G. D. Konidaris and A. G. Barto · 2009
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Reinforcement learning with videos: Combining offline observations with interaction
K. Schmeckpeper, O. Rybkin, K. Daniilidis, S. Levine, and C. Finn · 2011
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Sinkhorn distances: Lightspeed computation of optimal transport
M. Cuturi · 2013
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Cliquecnn: Deep unsupervised exemplar learning
M. A. Bautista, A. Sanakoyeu, E. Tikhoncheva, and B. Ommer · 2016
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K. Gregor, D. J. Rezende, and D. Wierstra · 2016
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Unsupervised perceptual rewards for imitation learning
P. Sermanet, K. Xu, and S. Levine · 2016
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Multi-level discovery of deep options
R. Fox, S. Krishnan, I. Stoica, and K. Goldberg · 2017
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Vision-based multi-task manipulation for inexpensive robots using end-to-end learning from demonstration
R. Rahmatizadeh, P. Abolghasemi, L. Bölöni, and S. Levine · 2017
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Deep imitation learning for complex manipulation tasks from virtual reality teleoperation
T. Zhang, Z. McCarthy, O. Jow, D. Lee, K. Goldberg, and P. Abbeel · 2017
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One-shot imitation learning
Y. Duan, M. Andrychowicz, B. C. Stadie, J. Ho, J. Schneider, I. Sutskever, P. Abbeel, and W. Zaremba · 2017
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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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Attention is all you need
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin · 2017
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Deep clustering for unsupervised learning of visual features
M. Caron, P. Bojanowski, A. Joulin, and M. Douze · 2018
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Diversity is all you need: Learning skills without a reward function
B. Eysenbach, A. Gupta, J. Ibarz, and S. Levine · 2018
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Expanding motor skills using relay networks
V. C. V. Kumar, S. Ha, and C. K. Liu · 2018
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Variational option discovery algorithms, 2018
J. Achiam, H. Edwards, D. Amodei, and P. Abbeel · 2018
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Learning an embedding space for transferable robot skills
K. Hausman, J. T. Springenberg, Z. Wang, N. M. O. Heess, and M. A. Riedmiller · 2018
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Hierarchical imitation and reinforcement learning, 2018
H. M. Le, N. Jiang, A. Agarwal, M. Dudík, Y. Yue, and H. D. I. au2 · 2018
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Taco: Learning task decomposition via temporal alignment for control
K. Shiarlis, M. Wulfmeier, S. Salter, S. Whiteson, and I. Posner · 2018
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Imitation from observation: Learning to imitate behaviors from raw video via context translation, 2018
Y. Liu, A. Gupta, P. Abbeel, and S. Levine · 2018
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One-shot imitation from observing humans via domain-adaptive meta-learning, 2018
T. Yu, C. Finn, A. Xie, S. Dasari, T. Zhang, P. Abbeel, and S. Levine · 2018
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One-shot hierarchical imitation learning of compound visuomotor tasks, 2018
T. Yu, P. Abbeel, S. Levine, and C. Finn · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova · 2018
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Time-contrastive networks: Self-supervised learning from video, 2018
P. Sermanet, C. Lynch, Y. Chebotar, J. Hsu, E. Jang, S. Schaal, and S. Levine · 2018
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Representation learning with contrastive predictive coding
A. v. d. Oord, Y. Li, and O. Vinyals · 2018
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Self-labelling via simultaneous clustering and representation learning
Y. M. Asano, C. Rupprecht, and A. Vedaldi · 2019
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Dynamics-aware unsupervised discovery of skills
A. Sharma, S. S. Gu, S. Levine, V. Kumar, and K. Hausman · 2019
SKID RAW: skill discovery from raw trajectories
D. Tanneberg, K. Ploeger, E. Rueckert, and J. Peters · 2021
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Parrot: Data-driven behavioral priors for reinforcement learning
A. Singh, H. Liu, G. Zhou, A. Yu, N. Rhinehart, and S. Levine · 2021
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Bottom-up skill discovery from unsegmented demonstrations for long-horizon robot manipulation
Y. Zhu, P. Stone, and Y. Zhu · 2021
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What matters in learning from offline human demonstrations for robot manipulation
A. Mandlekar, D. Xu, J. Wong, S. Nasiriany, C. Wang, R. Kulkarni, L. Fei-Fei, S. Savarese, Y. Zhu, and R. Mart’in-Mart’in · 2021
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Implicit behavioral cloning
P. Florence, C. Lynch, A. Zeng, O. Ramirez, A. Wahid, L. Downs, A. Wong, J. Lee, I. Mordatch, and J. Tompson · 2021
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Towards more generalizable one-shot visual imitation learning
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Self-supervised correspondence in visuomotor policy learning
P. R. Florence, L. Manuelli, and R. Tedrake · 2019
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Learning latent plans from play
C. Lynch, M. Khansari, T. Xiao, V. Kumar, J. Tompson, S. Levine, and P. Sermanet · 2019
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Iris: Implicit reinforcement without interaction at scale for learning control from offline robot manipulation data
A. Mandlekar, F. Ramos, B. Boots, L. Fei-Fei, A. Garg, and D. Fox · 2019
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Third-person visual imitation learning via decoupled hierarchical controller, 2019
P. Sharma, D. Pathak, and A. Gupta · 2019
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Graph-structured visual imitation
M. Sieb, X. Zhou, A. Huang, O. Kroemer, and K. Fragkiadaki · 2019
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Relay policy learning: Solving long-horizon tasks via imitation and reinforcement learning, 2019
A. Gupta, V. Kumar, C. Lynch, S. Levine, and K. Hausman · 2019
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Unsupervised learning of visual features by contrasting cluster assignments
M. Caron, I. Misra, J. Mairal, P. Goyal, P. Bojanowski, and A. Joulin · 2020
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Z. Mandi, F. Liu, K. Lee, and P. Abbeel · 2021
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Xirl: Cross-embodiment inverse reinforcement learning
K. Zakka, A. Zeng, P. R. Florence, J. Tompson, J. Bohg, and D. Dwibedi · 2021
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Concept2robot: Learning manipulation concepts from instructions and human demonstrations
L. Shao, T. Migimatsu, Q. Zhang, K. Yang, and J. Bohg · 2021
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Learning by watching: Physical imitation of manipulation skills from human videos
H. Xiong, Q. Li, Y.-C. Chen, H. Bharadhwaj, S. Sinha, and A. Garg · 2021
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Learning generalizable robotic reward functions from ”in-the-wild” human videos
A. S. Chen, S. Nair, and C. Finn · 2021
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Bridge data: Boosting generalization of robotic skills with cross-domain datasets, 2021
F. Ebert, Y. Yang, K. Schmeckpeper, B. Bucher, G. Georgakis, K. Daniilidis, C. Finn, and S. Levine · 2021
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Unsupervised reinforcement learning with contrastive intrinsic control
M. Laskin, H. Liu, X. B. Peng, D. Yarats, A. Rajeswaran, and P. Abbeel · 2022
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ASPire: Adaptive skill priors for reinforcement learning
M. Xu, M. Veloso, and S. Song · 2022
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Behavior transformers: Cloning k k modes with one stone
N. M. M. Shafiullah, Z. J. Cui, A. Altanzaya, and L. Pinto · 2022
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VIOLA: Object-centric imitation learning for vision-based robot manipulation
Y. Zhu, A. Joshi, P. Stone, and Y. Zhu · 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, J. Ibarz, B. Ichter, A. Irpan, T. Jackson, S. Jesmonth, N. Joshi, R. Julian, D. Kalashnikov, Y. Kuang, I. Leal, K.-H. Lee, S. Levine, Y. Lu, U. Malla, D. Manjunath, I. Mordatch, O. Nachum, C. Parada, J. Peralta, E. Perez, K. Pertsch, J. Quiambao, K. Rao, M. Ryoo, G. Salazar, P. Sanketi, K. Sayed, J. Singh, S. Sontakke, A. Stone, C. Tan, H. Tran, V. Vanhoucke, S. Vega, Q. Vuong, F. Xia, T. Xiao, P. Xu, S. Xu, T. Yu, and B. Zitkovich · 2022
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Masked visual pre-training for motor control
T. Xiao, I. Radosavovic, T. Darrell, and J. Malik · 2022
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Graph inverse reinforcement learning from diverse videos
S. Kumar, J. Zamora, N. Hansen, R. Jangir, and X. Wang · 2022
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Human-to-robot imitation in the wild
S. Bahl, A. Gupta, and D. Pathak · 2022
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R3m: A universal visual representation for robot manipulation, 2022
S. Nair, A. Rajeswaran, V. Kumar, C. Finn, and A. Gupta · 2022
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Diffusion policy: Visuomotor policy learning via action diffusion
C. Chi, S. Feng, Y. Du, Z. Xu, E. Cousineau, B. Burchfiel, and S. Song · 2023
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Imitating human behaviour with diffusion models
T. Pearce, T. Rashid, A. Kanervisto, D. Bignell, M. Sun, R. Georgescu, S. V. Macua, S. Z. Tan, I. Momennejad, K. Hofmann, and S. Devlin · 2023
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Goal-conditioned imitation learning using score-based diffusion policies
M. Reuss, M. X. Li, X. Jia, and R. Lioutikov · 2023
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Mimicplay: Long-horizon imitation learning by watching human play
C. Wang, L. J. Fan, J. Sun, R. Zhang, L. Fei-Fei, D. Xu, Y. Zhu, and A. Anandkumar · 2023
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