5 citations · 21 across the 13 of their papers we have counts for
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cs.LG2022★ 5 cited
Deep W-Networks: Solving Multi-Objective Optimisation Problems With Deep Reinforcement Learning
Jernej Hribar, Luke Hackett, Ivana Dusparic
In this paper, we build on advances introduced by the Deep Q-Networks (DQN) approach to extend the multi-objective tabular Reinforcement Learning (RL) algorithm W-learning to large…
cs.LG2020★ 2 cited
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…