2 papers
cs.LG2021
RAPID-RL: A Reconfigurable Architecture with Preemptive-Exits for Efficient Deep-Reinforcement Learning
Adarsh Kumar Kosta, Malik Aqeel Anwar, Priyadarshini Panda +2
Present-day Deep Reinforcement Learning (RL) systems show great promise towards building intelligent agents surpassing human-level performance. However, the computational complexit…
cs.LG2018
NAVREN-RL: Learning to fly in real environment via end-to-end deep reinforcement learning using monocular images
Malik Aqeel Anwar, Arijit Raychowdhury
We present NAVREN-RL, an approach to NAVigate an unmanned aerial vehicle in an indoor Real ENvironment via end-to-end reinforcement learning RL. A suitable reward function is desig…