Safe and Sample-Efficient Reinforcement Learning for Clustered Dynamic Environments
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Control Systems Letters"
DOI: 10.1109/lcsys.2021.3136486
Abstract: This letter proposes a safe and sample-efficient reinforcement learning (RL) framework to address two major challenges in developing applicable RL algorithms: satisfying safety constraints and efficiently learning with limited samples. To guarantee safety in real-world… read more here.
Keywords: sample efficient; clustered dynamic; reinforcement learning; safe sample ... See more keywords