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Human-AI shared control allows human to interact and collaborate with AI to accomplish control tasks in complex environments.
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Universal value function approximators
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End to end learning for self-driving cars
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Using artificial intelligence to augment human intelligence
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Interpretable learning for self-driving cars by visualizing causal attention
J. Kim and J. Canny · 2017
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Trial without error: Towards safe reinforcement learning via human intervention
W. Saunders, G. Sastry, A. Stuhlmueller, and O. Evans · 2017
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Proximal policy optimization algorithms
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Vector-based navigation using grid-like representations in artificial agents
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Gan dissection: Visualizing and understanding generative adversarial networks
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End-to-end driving via conditional imitation learning
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Human-centered autonomous vehicle systems: Principles of effective shared autonomy
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Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
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Hierarchical reinforcement learning with hindsight
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Neural probabilistic motor primitives for humanoid control
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Data-efficient hierarchical reinforcement learning
O. Nachum, S. Gu, H. Lee, and S. Levine · 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
Reinforcement learning based control of imitative policies for near-accident driving
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Reconstructing actions to explain deep reinforcement learning
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Urban driving with conditional imitation learning
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Benchmarking deep learning interpretability in time series predictions
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Shared autonomy with learned latent actions
H. J. Jeon, D. P. Losey, and D. Sadigh · 2020
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Shared autonomy via deep reinforcement learning
S. Reddy, A. D. Dragan, and S. Levine · 2018
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High-dimensional continuous control using generalized advantage estimation, 2018
J. Schulman, P. Moritz, S. Levine, M. Jordan, and P. Abbeel · 2018
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An atari model zoo for analyzing, visualizing, and comparing deep reinforcement learning agents
F. P. Such, V. Madhavan, R. Liu, R. Wang, P. S. Castro, Y. Li, J. Zhi, L. Schubert, M. G. Bellemare, J. Clune, et al · 2018
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Reinforcement learning: An introduction
R. S. Sutton and A. G. Barto · 2018
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Deep tamer: Interactive agent shaping in high-dimensional state spaces
G. Warnell, N. Waytowich, V. Lawhern, and P. Stone · 2018
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Feedback control for cassie with deep reinforcement learning
Z. Xie, G. Berseth, P. Clary, J. Hurst, and M. van de Panne · 2018
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Visual interpretability for deep learning: a survey
Q.-s. Zhang and S.-c. Zhu · 2018
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Learning quadrupedal locomotion over challenging terrain
J. Lee, J. Hwangbo, L. Wellhausen, V. Koltun, and M. Hutter · 2020
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A survey of data-driven and knowledge-aware explainable ai
X.-H. Li, C. C. Cao, Y. Shi, W. Bai, H. Gao, L. Qiu, C. Wang, Y. Gao, S. Zhang, X. Xue, et al · 2020
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Human-in-the-loop imitation learning using remote teleoperation
A. Mandlekar, D. Xu, R. Martín-Martín, Y. Zhu, L. Fei-Fei, and S. Savarese · 2020
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Learning human objectives by evaluating hypothetical behavior
S. Reddy, A. Dragan, S. Levine, S. Legg, and J. Leike · 2020
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Residual policy learning for shared autonomy
C. Schaff and M. R. Walter · 2020
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Learning from interventions
J. Spencer, S. Choudhury, M. Barnes, M. Schmittle, M. Chiang, P. Ramadge, and S. Srinivasa · 2020
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Inducing functions through reinforcement learning without task specification
J. Cho, D.-H. Lee, and Y.-G. Yoon · 2021
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Machine versus human attention in deep reinforcement learning tasks
S. Guo, R. Zhang, B. Liu, Y. Zhu, D. Ballard, M. Hayhoe, and P. Stone · 2021
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Evaluating the robustness of collaborative agents
P. Knott, M. Carroll, S. Devlin, K. Ciosek, K. Hofmann, A. D. Dragan, and R. Shah · 2021
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Rma: Rapid motor adaptation for legged robots
A. Kumar, Z. Fu, D. Pathak, and J. Malik · 2021
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Metadrive: Composing diverse driving scenarios for generalizable reinforcement learning
Q. Li, Z. Peng, Z. Xue, Q. Zhang, and B. Zhou · 2021
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Learning high-speed flight in the wild
A. Loquercio, E. Kaufmann, R. Ranftl, M. Müller, V. Koltun, and D. Scaramuzza · 2021
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Isaac gym: High performance gpu-based physics simulation for robot learning
V. Makoviychuk, L. Wawrzyniak, Y. Guo, M. Lu, K. Storey, M. Macklin, D. Hoeller, N. Rudin, A. Allshire, A. Handa, et al · 2021
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Explanations in autonomous driving: A survey
D. Omeiza, H. Webb, M. Jirotka, and L. Kunze · 2021
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Safe driving via expert guided policy optimization
Z. Peng, Q. Li, C. Liu, and B. Zhou · 2021
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Closed-form factorization of latent semantics in gans
Y. Shen and B. Zhou · 2021
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Human-in-the-loop deep reinforcement learning with application to autonomous driving
J. Wu, Z. Huang, C. Huang, Z. Hu, P. Hang, Y. Xing, and C. Lv · 2021
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Generative hierarchical features from synthesizing images
Y. Xu, Y. Shen, J. Zhu, C. Yang, and B. Zhou · 2021
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Embodiment perspective of reward definition for behavioural homeostasis
N. Yoshida, T. Daikoku, Y. Nagai, and Y. Kuniyoshi · 2021
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Explainability of vision-based autonomous driving systems: Review and challenges
É. Zablocki, H. Ben-Younes, P. Pérez, and M. Cord · 2021
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Recent advances in leveraging human guidance for sequential decision-making tasks
R. Zhang, F. Torabi, G. Warnell, and P. Stone · 2021
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Learning to walk in minutes using massively parallel deep reinforcement learning
N. Rudin, D. Hoeller, P. Reist, and M. Hutter · 2022
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