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EPISODE · Mar 22, 2021 · 50 MIN

Nathan Lambert

from TalkRL: The Reinforcement Learning Podcast · host Robin Ranjit Singh Chauhan

Nathan Lambert is a PhD Candidate at UC Berkeley. Featured References Learning Accurate Long-term Dynamics for Model-based Reinforcement Learning Nathan O. Lambert, Albert Wilcox, Howard Zhang, Kristofer S. J. Pister, Roberto Calandra Objective Mismatch in Model-based Reinforcement Learning Nathan Lambert, Brandon Amos, Omry Yadan, Roberto Calandra Low Level Control of a Quadrotor with Deep Model-Based Reinforcement Learning Nathan O. Lambert, Daniel S. Drew, Joseph Yaconelli, Roberto Calandra, Sergey Levine, Kristofer S.J. Pister On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning Baohe Zhang, Raghu Rajan, Luis Pineda, Nathan Lambert, André Biedenkapp, Kurtland Chua, Frank Hutter, Roberto Calandra Additional References Nathan Lambert's blog Nathan Lambert on Google scholar 

Nathan Lambert on Model-based RL, Trajectory-based models, Quadrotor control, Hyperparameter Optimization for MBRL, RL vs PID control, and more!

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Nathan Lambert

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This episode is 50 minutes long.

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This episode was published on March 22, 2021.

What is this episode about?

Nathan Lambert is a PhD Candidate at UC Berkeley. Featured References Learning Accurate Long-term Dynamics for Model-based Reinforcement Learning Nathan O. Lambert, Albert Wilcox, Howard Zhang, Kristofer S. J. Pister, Roberto Calandra Objective...

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