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A crucial capability of real-world intelligent agents is their ability to plan a sequence of actions to achieve their goals in the visual world.
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Actions ~ transformations
X. Wang, A. Farhadi, and A. Gupta · 2016
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Learning to act by predicting the future
A. Dosovitskiy and V. Koltun · 2017
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Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates
S. Gu, E. Holly, T. Lillicrap, and S. Levine · 2017
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Inferring the latent structure of human decision-making from raw visual inputs
Y. Li, J. Song, and S. Ermon · 2017
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Target-driven visual navigation in indoor scenes using deep reinforcement learning
Y. Zhu, R. Mottaghi, E. Kolve, J. J. Lim, A. Gupta, L. Fei-Fei, and A. Farhadi · 2017
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