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Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL.

A. Nagabandi, C. Finn, and S. Levine. ICLR (Poster), OpenReview.net, (2019)

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Neural Network Dynamics Models for Control of Under-actuated Legged Millirobots.A. Nagabandi, G. Yang, T. Asmar, G. Kahn, S. Levine, and R. Fearing. CoRR, (2017)Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning.A. Nagabandi, G. Kahn, R. Fearing, and S. Levine. ICRA, page 7559-7566. IEEE, (2018)Learning to Adapt in Dynamic, Real-World Environments through Meta-Reinforcement Learning.A. Nagabandi, I. Clavera, S. Liu, R. Fearing, P. Abbeel, S. Levine, and C. Finn. ICLR (Poster), OpenReview.net, (2019)Trust During Robot-Assisted Navigation.E. Mason, A. Nagabandi, A. Steinfeld, and C. Bruggeman. AAAI Spring Symposium: Trust and Autonomous Systems, volume SS-13-07 of AAAI Technical Report, AAAI, (2013)Learning to Adapt: Meta-Learning for Model-Based Control.I. Clavera, A. Nagabandi, R. Fearing, P. Abbeel, S. Levine, and C. Finn. CoRR, (2018)Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning.A. Nagabandi, G. Kahn, R. Fearing, and S. Levine. CoRR, (2017)Expressive Robot Motion Timing.A. Zhou, D. Hadfield-Menell, A. Nagabandi, and A. Dragan. CoRR, (2018)Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RL.A. Nagabandi, C. Finn, and S. Levine. CoRR, (2018)Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model.A. Lee, A. Nagabandi, P. Abbeel, and S. Levine. CoRR, (2019)A path planning algorithm for single-ended continuous planar robotic ribbon folding.A. Nagabandi, L. Wang, and R. Fearing. IROS, page 3239-3246. IEEE, (2016)

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Disambiguation of "Nagabandi, Anusha"

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Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL.

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Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL.