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Most recent successes in robot reinforcement learning involve learning a specialized single-task agent.
Visualizing data using t-sne
L. Van der Maaten and G. Hinton · 2008
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Sample complexity of multi-task reinforcement learning
E. Brunskill and L. Li · 2013
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The arcade learning environment: An evaluation platform for general agents
M. G. Bellemare, Y. Naddaf, J. Veness, and M. Bowling · 2013
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Perceptual losses for real-time style transfer and super-resolution
J. Johnson, A. Alahi, and L. Fei-Fei · 2016
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Autoencoding beyond pixels using a learned similarity metric
A. B. L. Larsen, S. K. Sønderby, H. Larochelle, and O. Winther · 2016
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Policy distillation
A. A. Rusu, S. G. Colmenarejo, C. Gulcehre, G. Desjardins, J. Kirkpatrick, R. Pascanu, V. Mnih, K. Kavukcuoglu, and R. Hadsell · 2016
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Actor-mimic: Deep multitask and transfer reinforcement learning
E. Parisotto, L. J. Ba, and R. Salakhutdinov · 2016
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Listen, attend, and walk: Neural mapping of navigational instructions to action sequences
H. Mei, M. Bansal, and M. Walter · 2016
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Transferring end-to-end visuomotor control from simulation to real world for a multi-stage task
S. James, A. J. Davison, and E. Johns · 2017
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Neural discrete representation learning
A. Van Den Oord, O. Vinyals, et al · 2017
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Mapping instructions and visual observations to actions with reinforcement learning
D. Misra, J. Langford, and Y. Artzi · 2017
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Sim-to-real transfer of robotic control with dynamics randomization
X. B. Peng, M. Andrychowicz, W. Zaremba, and P. Abbeel · 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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Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor, 2018
T. Haarnoja, A. Zhou, P. Abbeel, and S. Levine · 2018
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Solving rubik’s cube with a robot hand
I. Akkaya, M. Andrychowicz, M. Chociej, M. Litwin, B. McGrew, A. Petron, A. Paino, M. Plappert, G. Powell, R. Ribas, et al · 2019
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Learning agile and dynamic motor skills for legged robots
J. Hwangbo, J. Lee, A. Dosovitskiy, D. Bellicoso, V. Tsounis, V. Koltun, and M. Hutter · 2019
Cited alongside, same era.
Challenges of real-world reinforcement learning, 2019
G. Dulac-Arnold, D. Mankowitz, and T. Hester · 2019
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Sentence-BERT: Sentence embeddings using Siamese BERT-networks
N. Reimers and I. Gurevych · 2019
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Multi-task deep reinforcement learning with popart
M. Hessel, H. Soyer, L. Espeholt, W. Czarnecki, S. Schmitt, and H. Van Hasselt · 2019
Cited alongside, same era.
Language as an abstraction for hierarchical deep reinforcement learning
Y. Jiang, S. S. Gu, K. P. Murphy, and C. Finn · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
A. Radford, J. Wu, R. Child, D. Luan, D. Amodei, I. Sutskever, et al · 2019
Calvin: A benchmark for language-conditioned policy learning for long-horizon robot manipulation tasks
O. Mees, L. Hermann, E. Rosete-Beas, and W. Burgard · 2022
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What matters in language conditioned robotic imitation learning over unstructured data
O. Mees, L. Hermann, and W. Burgard · 2022
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Do as i can, not as i say: Grounding language in robotic affordances
M. Ahn, A. Brohan, N. Brown, Y. Chebotar, O. Cortes, B. David, C. Finn, C. Fu, K. Gopalakrishnan, K. Hausman, et al · 2022
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Lila: Language-informed latent actions
S. Karamcheti, M. Srivastava, P. Liang, and D. Sadigh · 2022
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Planning with diffusion for flexible behavior synthesis, 2022
M. Janner, Y. Du, J. B. Tenenbaum, and S. Levine · 2022
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Cited alongside, same era.
PyTorch: An Imperative Style, High-Performance Deep Learning Library , page 8024–8035
A. Paszke, S. Gross, F. Massa, A. Lerer, J. Bradbury, G. Chanan, T. Killeen, Z. Lin, N. Gimelshein, L. Antiga, A. Desmaison, A. Kopf, E. Yang, Z. DeVito, M. Raison, A. Tejani, S. Chilamkurthy, B. Steiner, L. Fang, J. Bai, and S. Chintala · 2019
Cited alongside, same era.
Dream to control: Learning behaviors by latent imagination
D. Hafner, T. Lillicrap, J. Ba, and M. Norouzi · 2020
Cited alongside, same era.
Language models are few-shot learners, 2020
T. B. Brown, B. Mann, N. Ryder, M. Subbiah, J. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, S. Agarwal, A. Herbert-Voss, G. Krueger, T. Henighan, R. Child, A. Ramesh, D. M. Ziegler, J. Wu, C. Winter, C. Hesse, M. Chen, E. Sigler, M. Litwin, S. Gray, B. Chess, J. Clark, C. Berner, S. McCandlish, A. Radford, I. Sutskever, and D. Amodei · 2020
Cited alongside, same era.
Sharing knowledge in multi-task deep reinforcement learning
C. D’Eramo, D. Tateo, A. Bonarini, M. Restelli, and J. Peters · 2020
Cited alongside, same era.
Multi-task reinforcement learning with soft modularization
R. Yang, H. Xu, Y. WU, and X. Wang · 2020
Cited alongside, same era.
Language-conditioned imitation learning for robot manipulation tasks
S. Stepputtis, J. Campbell, M. Phielipp, S. Lee, C. Baral, and H. Ben Amor · 2020
Cited alongside, same era.
Transformers are sample-efficient world models
V. Micheli, E. Alonso, and F. Fleuret · 2023
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Latent plans for task-agnostic offline reinforcement learning
E. Rosete-Beas, O. Mees, G. Kalweit, J. Boedecker, and W. Burgard · 2023
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Sayplan: Grounding large language models using 3d scene graphs for scalable robot task planning
K. Rana, J. Haviland, S. Garg, J. Abou-Chakra, I. Reid, and N. Suenderhauf · 2023
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Chatgpt empowered long-step robot control in various environments: A case application
N. Wake, A. Kanehira, K. Sasabuchi, J. Takamatsu, and K. Ikeuchi · 2023
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Progprompt: Generating situated robot task plans using large language models
I. Singh, V. Blukis, A. Mousavian, A. Goyal, D. Xu, J. Tremblay, D. Fox, J. Thomason, and A. Garg · 2023
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Vision-language models as success detectors
Y. Du, K. Konyushkova, M. Denil, A. Raju, J. Landon, F. Hill, N. de Freitas, and S. Cabi · 2023
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Roco: Dialectic multi-robot collaboration with large language models
Z. Mandi, S. Jain, and S. Song · 2023
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Palm-e: an embodied multimodal language model
D. Driess, F. Xia, M. S. Sajjadi, C. Lynch, A. Chowdhery, B. Ichter, A. Wahid, J. Tompson, Q. Vuong, T. Yu, et al · 2023
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Rt-2: Vision-language-action models transfer web knowledge to robotic control
B. Zitkovich, T. Yu, S. Xu, P. Xu, T. Xiao, F. Xia, J. Wu, P. Wohlhart, S. Welker, A. Wahid, et al · 2023
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Lm-nav: Robotic navigation with large pre-trained models of language, vision, and action
D. Shah, B. Osiński, S. Levine, et al · 2023
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On the role of the action space in robot manipulation learning and sim-to-real transfer
E. Aljalbout, F. Frank, M. Karl, and P. van der Smagt · 2024
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