158 citations · 158 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 158 cited
Explainable Deep Reinforcement Learning: State of the Art and Challenges
George A. Vouros
Interpretability, explainability and transparency are key issues to introducing Artificial Intelligence methods in many critical domains: This is important due to ethical concerns…
cs.LG2023
XDQN: Inherently Interpretable DQN through Mimicking
Andreas Kontogiannis, George Vouros
Although deep reinforcement learning (DRL) methods have been successfully applied in challenging tasks, their application in real-world operational settings is challenged by method…
cs.IR2014
Semantic Integration & Single-Site Opening of Multiple Governmental Data Sources
Konstantinos Kotis, Iraklis Athanasakis, George Vouros
In many cases, government data is still "locked" in several "data silos", even within the boundaries of a single (inter-)national public organization with disparate and distributed…