8 code implementations • 24 Oct 2019 • Tianhe Yu, Deirdre Quillen, Zhanpeng He, Ryan Julian, Avnish Narayan, Hayden Shively, Adithya Bellathur, Karol Hausman, Chelsea Finn, Sergey Levine
Therefore, if the aim of these methods is to enable faster acquisition of entirely new behaviors, we must evaluate them on task distributions that are sufficiently broad to enable generalization to new behaviors.
Ranked #1 on Meta-Learning on ML10
7 code implementations • ICLR Workshop LLD 2019 • Kate Rakelly, Aurick Zhou, Deirdre Quillen, Chelsea Finn, Sergey Levine
In our approach, we perform online probabilistic filtering of latent task variables to infer how to solve a new task from small amounts of experience.
1 code implementation • 27 Jun 2018 • Dmitry Kalashnikov, Alex Irpan, Peter Pastor, Julian Ibarz, Alexander Herzog, Eric Jang, Deirdre Quillen, Ethan Holly, Mrinal Kalakrishnan, Vincent Vanhoucke, Sergey Levine
In this paper, we study the problem of learning vision-based dynamic manipulation skills using a scalable reinforcement learning approach.
1 code implementation • 28 Feb 2018 • Deirdre Quillen, Eric Jang, Ofir Nachum, Chelsea Finn, Julian Ibarz, Sergey Levine
In this paper, we explore deep reinforcement learning algorithms for vision-based robotic grasping.
no code implementations • 7 Mar 2016 • Sergey Levine, Peter Pastor, Alex Krizhevsky, Deirdre Quillen
We describe a learning-based approach to hand-eye coordination for robotic grasping from monocular images.