81 citations · 93 across the 11 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2022★ 4 cited
CT-DQN: Control-Tutored Deep Reinforcement Learning
Francesco De Lellis, Marco Coraggio, Giovanni Russo +2
One of the major challenges in Deep Reinforcement Learning for control is the need for extensive training to learn the policy. Motivated by this, we present the design of the Contr…
cs.LG2019★ 1 cited
Control-Tutored Reinforcement Learning: an application to the Herding Problem
Francesco De Lellis, Fabrizia Auletta, Giovanni Russo +1
In this extended abstract we introduce a novel control-tutored Q-learning approach (CTQL) as part of the ongoing effort in developing model-based and safe RL for continuous state s…