158 citations · 183 across the 14 of their papers we have counts for
4 papers · 1 filter
Learning safe, constrained policies via imitation learning: Connection to Probabilistic Inference and a Naive Algorithm
George Papadopoulos, George A. Vouros
This article introduces an imitation learning method for learning maximum entropy policies that comply with constraints demonstrated by expert trajectories executing a task. The fo…
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…
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…
Data Driven Aircraft Trajectory Prediction with Deep Imitation Learning
Alevizos Bastas, Theocharis Kravaris, George A. Vouros
The current Air Traffic Management (ATM) system worldwide has reached its limits in terms of predictability, efficiency and cost effectiveness. Different initiatives worldwide prop…