Recovery RL: Safe Reinforcement Learning With Learned Recovery Zones-Reference-Cited by-同舟云学术

Recovery RL: Safe Reinforcement Learning With Learned Recovery Zones

Published:2021-07 Issue:3 Volume:6 Page:4915-4922
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Thananjeyan Brijen^ORCID,Balakrishna Ashwin^ORCID,Nair Suraj^ORCID,Luo Michael,Srinivasan Krishnan^ORCID,Hwang Minho^ORCID,Gonzalez Joseph E.,Ibarz Julian,Finn Chelsea^ORCID,Goldberg Ken^ORCID

Funder

AUTOLAB at UC Berkeley in affiliation with the Berkeley AI Research (BAIR) Lab

Real-Time Intelligent Secure Execution (RISE) Lab

Google Brain Robotics

Stanford AI Research Lab.

SAIL-Toyota Research initiative

Scalable Collaborative Human-Robot Learning (SCHooL) Project

NSF National Robotics Initiative

Google

Siemens

Amazon Robotics

Toyota Research Institute

Nvidia

NSF GRFPs

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/7083369/9399748/09392290.pdf?arnumber=9392290

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