12 citations · 44 across the 41 of their papers we have counts for
6 papers · 1 filter
Iterative Reward Shaping using Human Feedback for Correcting Reward Misspecification
Jasmina Gajcin, James McCarthy, Rahul Nair +3
A well-defined reward function is crucial for successful training of an reinforcement learning (RL) agent. However, defining a suitable reward function is a notoriously challenging…
Density-Aware Reinforcement Learning to Optimise Energy Efficiency in UAV-Assisted Networks
Babatunji Omoniwa, Boris Galkin, Ivana Dusparic
Unmanned aerial vehicles (UAVs) serving as aerial base stations can be deployed to provide wireless connectivity to mobile users, such as vehicles. However, the density of vehicles…
Reservation of Virtualized Resources with Optimistic Online Learning
Jean-Baptiste Monteil, George Iosifidis, Ivana Dusparic
The virtualization of wireless networks enables new services to access network resources made available by the Network Operator (NO) through a Network Slicing market. The different…
Prevalence of Code Smells in Reinforcement Learning Projects
Nicolás Cardozo, Ivana Dusparic, Christian Cabrera
Reinforcement Learning (RL) is being increasingly used to learn and adapt application behavior in many domains, including large-scale and safety critical systems, as for example, a…
RACCER: Towards Reachable and Certain Counterfactual Explanations for Reinforcement Learning
Jasmina Gajcin, Ivana Dusparic
While reinforcement learning (RL) algorithms have been successfully applied to numerous tasks, their reliance on neural networks makes their behavior difficult to understand and tr…
Expert-Free Online Transfer Learning in Multi-Agent Reinforcement Learning
Alberto Castagna, Ivana Dusparic
Transfer learning in Reinforcement Learning (RL) has been widely studied to overcome training issues of Deep-RL, i.e., exploration cost, data availability and convergence time, by…