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MELD: Meta-Reinforcement Learning from Images via Latent State Models
Meta-reinforcement learning algorithms can enable autonomous agents, suc...
10/26/2020 ∙ by Tony Z. Zhao, et al. ∙
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Deep Dynamics Models for Learning Dexterous Manipulation
Dexterous multi-fingered hands can provide robots with the ability to fl...
09/25/2019 ∙ by Anusha Nagabandi, et al. ∙
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Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model
Deep reinforcement learning (RL) algorithms can use high-capacity deep n...
07/01/2019 ∙ by Alex X. Lee, et al. ∙
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Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RL
Humans and animals can learn complex predictive models that allow them t...
12/18/2018 ∙ by Anusha Nagabandi, et al. ∙
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Learning to Adapt: Meta-Learning for Model-Based Control
Although reinforcement learning methods can achieve impressive results i...
03/30/2018 ∙ by Ignasi Clavera, et al. ∙
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Expressive Robot Motion Timing
Our goal is to enable robots to time their motion in a way that is purpo...
02/05/2018 ∙ by Allan Zhou, et al. ∙
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Neural Network Dynamics Models for Control of Under-actuated Legged Millirobots
Millirobots are a promising robotic platform for many applications due t...
11/14/2017 ∙ by Anusha Nagabandi, et al. ∙
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Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning
Model-free deep reinforcement learning algorithms have been shown to be ...
08/08/2017 ∙ by Anusha Nagabandi, et al. ∙
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