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cs.LG2024
SHIRE: Enhancing Sample Efficiency using Human Intuition in REinforcement Learning
Amogh Joshi, Adarsh Kumar Kosta, Kaushik Roy
The ability of neural networks to perform robotic perception and control tasks such as depth and optical flow estimation, simultaneous localization and mapping (SLAM), and automati…
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…