2 citations · 2 across the 2 of their papers we have counts for
3 papers
Enabling Deep Reinforcement Learning on Energy Constrained Devices at the Edge of the Network
Jernej Hribar, Ivana Dusparic
Deep Reinforcement Learning (DRL) solutions are becoming pervasive at the edge of the network as they enable autonomous decision-making in a dynamic environment. However, to be abl…
Energy Aware Deep Reinforcement Learning Scheduling for Sensors Correlated in Time and Space
Jernej Hribar, Andrei Marinescu, Alessandro Chiumento +1
Millions of battery-powered sensors deployed for monitoring purposes in a multitude of scenarios, e.g., agriculture, smart cities, industry, etc., require energy-efficient solution…
Using Deep Q-learning To Prolong the Lifetime of Correlated Internet of Things Devices
Jernej Hribar, Andrei Marinescu, George A. Ropokis +1
Battery-powered sensors deployed in the Internet of Things (IoT) require energy-efficient solutions to prolong their lifetime. When these sensors observe a physical phenomenon dist…