RL&more@DEI*
*Research group part of the department of Information Engineering from the University of Padova
Who we are
Our research group at the Department of Information Engineering (DEI) is dedicated to fostering a collaborative community focused on advancing reinforcement learning. Beyond our primary emphasis on reinforcement learning, our researchers actively explore key domains such as continual learning, fairness, explainability, and anomaly detection. Through regular meetings, seminars, and collaborative initiatives, we create an intellectually stimulating environment within DEI. This not only enhances individual research pursuits but also contributes significantly to the broader academic and technological landscape. Our unified goal is to advance knowledge in reinforcement learning and its intersecting domains, positioning ourselves at the forefront of cutting-edge research in artificial intelligence.
Collaboration
Foster interdisciplinary cooperation to tackle challenging RL problems collectively.
Support
Provide resources, mentorship, and guidance for newcomers and experienced practitioners.
Knowledge Exchange
Encourage open discussions and idea-sharing to enrich the RL discourse.
Our latest publications
Here you'll find our latest publication about reinforcement learning, continual learning, fairness, explainability, and anomaly detection. This work reflects our ongoing commitment to advancing knowledge in artificial intelligence.
1. Explainable isolation forest
A study on how to improve isolation forest keeping their properties about explainability
2. Anomaly detection
Indeed we cover also anomaly detection, applying the latest technologies on hydroelectric dams to detect failures
3. Fair continual learning
Exploring the word of continual learning with a focus on keeping the model fair
4. MARL for mobility
Applying latest Multi Agent Reinforcement Learning techniques on the topic of smart mobility