149 citations · 263 across the 21 of their papers we have counts for
6 papers · 1 filter
FRL-FI: Transient Fault Analysis for Federated Reinforcement Learning-Based Navigation Systems
Zishen Wan, Aqeel Anwar, Abdulrahman Mahmoud +4
Swarm intelligence is being increasingly deployed in autonomous systems, such as drones and unmanned vehicles. Federated reinforcement learning (FRL), a key swarm intelligence para…
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…
Multi-Task Federated Reinforcement Learning with Adversaries
Aqeel Anwar, Arijit Raychowdhury
Reinforcement learning algorithms, just like any other Machine learning algorithm pose a serious threat from adversaries. The adversaries can manipulate the learning algorithm resu…
Hardware-aware Pruning of DNNs using LFSR-Generated Pseudo-Random Indices
Foroozan Karimzadeh, Ningyuan Cao, Brian Crafton +2
Deep neural networks (DNNs) have been emerged as the state-of-the-art algorithms in broad range of applications. To reduce the memory foot-print of DNNs, in particular for embedded…
Autonomous Navigation via Deep Reinforcement Learning for Resource Constraint Edge Nodes using Transfer Learning
Aqeel Anwar, Arijit Raychowdhury
Smart and agile drones are fast becoming ubiquitous at the edge of the cloud. The usage of these drones are constrained by their limited power and compute capability. In this paper…
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…